From 74e536411c4c4d94ba30b93f7072196437b2c3b0 Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Wed, 6 Oct 2021 20:25:11 +0530
Subject: [PATCH 01/53] Update README.md

---
 README.md | 4 ++++
 1 file changed, 4 insertions(+)

diff --git a/README.md b/README.md
index 7dd5272956ae1..0b0cb7c5e2550 100644
--- a/README.md
+++ b/README.md
@@ -391,6 +391,10 @@ The lightning community is maintained by
 - [10+ core contributors](https://pytorch-lightning.readthedocs.io/en/latest/governance.html) who are all a mix of professional engineers, Research Scientists, and Ph.D. students from top AI labs.
 - 480+ active community contributors.
 
+(You can create new features in PyTorch lightning.)[https://github.com/PyTorchLightning/pytorch-lightning/projects]
+  
+(You can solve issues in our github issues tab.)[https://github.com/PyTorchLightning/pytorch-lightning/issues]
+  
 Want to help us build Lightning and reduce boilerplate for thousands of researchers? [Learn how to make your first contribution here](https://devblog.pytorchlightning.ai/quick-contribution-guide-86d977171b3a)
 
 Lightning is also part of the [PyTorch ecosystem](https://pytorch.org/ecosystem/) which requires projects to have solid testing, documentation and support.

From e0af7c26380f8a08eb7f1b01c8ebad8704803632 Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Wed, 6 Oct 2021 20:26:42 +0530
Subject: [PATCH 02/53] Update README.md

---
 README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index 0b0cb7c5e2550..83b126a9e626f 100644
--- a/README.md
+++ b/README.md
@@ -391,9 +391,9 @@ The lightning community is maintained by
 - [10+ core contributors](https://pytorch-lightning.readthedocs.io/en/latest/governance.html) who are all a mix of professional engineers, Research Scientists, and Ph.D. students from top AI labs.
 - 480+ active community contributors.
 
-(You can create new features in PyTorch lightning.)[https://github.com/PyTorchLightning/pytorch-lightning/projects]
+[You can create new features in PyTorch lightning.](https://github.com/PyTorchLightning/pytorch-lightning/projects)
   
-(You can solve issues in our github issues tab.)[https://github.com/PyTorchLightning/pytorch-lightning/issues]
+[You can solve issues in our github issues tab.](https://github.com/PyTorchLightning/pytorch-lightning/issues)
   
 Want to help us build Lightning and reduce boilerplate for thousands of researchers? [Learn how to make your first contribution here](https://devblog.pytorchlightning.ai/quick-contribution-guide-86d977171b3a)
 

From b2a137254c7d601573fd12b9e1bac84873ebadf5 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Wed, 6 Oct 2021 15:00:02 +0000
Subject: [PATCH 03/53] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index 83b126a9e626f..a07b81480d624 100644
--- a/README.md
+++ b/README.md
@@ -392,9 +392,9 @@ The lightning community is maintained by
 - 480+ active community contributors.
 
 [You can create new features in PyTorch lightning.](https://github.com/PyTorchLightning/pytorch-lightning/projects)
-  
+
 [You can solve issues in our github issues tab.](https://github.com/PyTorchLightning/pytorch-lightning/issues)
-  
+
 Want to help us build Lightning and reduce boilerplate for thousands of researchers? [Learn how to make your first contribution here](https://devblog.pytorchlightning.ai/quick-contribution-guide-86d977171b3a)
 
 Lightning is also part of the [PyTorch ecosystem](https://pytorch.org/ecosystem/) which requires projects to have solid testing, documentation and support.

From 864b4005204626b32d4d6fa4b70317fb274fda6f Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Wed, 6 Oct 2021 23:23:14 +0530
Subject: [PATCH 04/53] Create evaluation.py

---
 pytorch_lightning/utilities/evaluation.py | 20 ++++++++++++++++++++
 1 file changed, 20 insertions(+)
 create mode 100644 pytorch_lightning/utilities/evaluation.py

diff --git a/pytorch_lightning/utilities/evaluation.py b/pytorch_lightning/utilities/evaluation.py
new file mode 100644
index 0000000000000..e387f4b7a81d4
--- /dev/null
+++ b/pytorch_lightning/utilities/evaluation.py
@@ -0,0 +1,20 @@
+import torch
+import torchvision
+
+def get_loss(model,X,y,criterion):
+    preds = model(X)
+    loss = criterion(preds,y)
+    return loss.item()
+  
+def get_accuracy(model,X,y):
+    preds = model(X)
+    correct = 0
+    total = 0
+    for pred,yb in zip(preds,y):
+        pred = int(torch.argmax(pred))
+        yb = int(torch.argmax(yb))
+        if pred == yb:
+            correct += 1
+        total += 1
+    acc = round(correct/total,3)*100
+    return acc

From 9e74636534843463f7dd22b36a100bbd8cbb6767 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Wed, 6 Oct 2021 17:54:26 +0000
Subject: [PATCH 05/53] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 pytorch_lightning/utilities/evaluation.py | 14 ++++++++------
 1 file changed, 8 insertions(+), 6 deletions(-)

diff --git a/pytorch_lightning/utilities/evaluation.py b/pytorch_lightning/utilities/evaluation.py
index e387f4b7a81d4..09c84faf6e453 100644
--- a/pytorch_lightning/utilities/evaluation.py
+++ b/pytorch_lightning/utilities/evaluation.py
@@ -1,20 +1,22 @@
 import torch
 import torchvision
 
-def get_loss(model,X,y,criterion):
+
+def get_loss(model, X, y, criterion):
     preds = model(X)
-    loss = criterion(preds,y)
+    loss = criterion(preds, y)
     return loss.item()
-  
-def get_accuracy(model,X,y):
+
+
+def get_accuracy(model, X, y):
     preds = model(X)
     correct = 0
     total = 0
-    for pred,yb in zip(preds,y):
+    for pred, yb in zip(preds, y):
         pred = int(torch.argmax(pred))
         yb = int(torch.argmax(yb))
         if pred == yb:
             correct += 1
         total += 1
-    acc = round(correct/total,3)*100
+    acc = round(correct / total, 3) * 100
     return acc

From 818e5fee81c671fa64b305c8d4bf90f0f66319d7 Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Wed, 6 Oct 2021 23:26:45 +0530
Subject: [PATCH 06/53] Update README.md

---
 README.md | 4 ----
 1 file changed, 4 deletions(-)

diff --git a/README.md b/README.md
index a07b81480d624..7dd5272956ae1 100644
--- a/README.md
+++ b/README.md
@@ -391,10 +391,6 @@ The lightning community is maintained by
 - [10+ core contributors](https://pytorch-lightning.readthedocs.io/en/latest/governance.html) who are all a mix of professional engineers, Research Scientists, and Ph.D. students from top AI labs.
 - 480+ active community contributors.
 
-[You can create new features in PyTorch lightning.](https://github.com/PyTorchLightning/pytorch-lightning/projects)
-
-[You can solve issues in our github issues tab.](https://github.com/PyTorchLightning/pytorch-lightning/issues)
-
 Want to help us build Lightning and reduce boilerplate for thousands of researchers? [Learn how to make your first contribution here](https://devblog.pytorchlightning.ai/quick-contribution-guide-86d977171b3a)
 
 Lightning is also part of the [PyTorch ecosystem](https://pytorch.org/ecosystem/) which requires projects to have solid testing, documentation and support.

From 5f86d08188baabac2f3cae6aed70146b4954fbd4 Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Wed, 6 Oct 2021 23:34:21 +0530
Subject: [PATCH 07/53] Update evaluation.py

---
 pytorch_lightning/utilities/evaluation.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/pytorch_lightning/utilities/evaluation.py b/pytorch_lightning/utilities/evaluation.py
index 09c84faf6e453..30fbad51c3bae 100644
--- a/pytorch_lightning/utilities/evaluation.py
+++ b/pytorch_lightning/utilities/evaluation.py
@@ -1,6 +1,4 @@
 import torch
-import torchvision
-
 
 def get_loss(model, X, y, criterion):
     preds = model(X)

From 24136291205134012d82bf55fc6e4750d52ff5cf Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Wed, 6 Oct 2021 18:05:33 +0000
Subject: [PATCH 08/53] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 pytorch_lightning/utilities/evaluation.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/pytorch_lightning/utilities/evaluation.py b/pytorch_lightning/utilities/evaluation.py
index 30fbad51c3bae..cb029a82f2681 100644
--- a/pytorch_lightning/utilities/evaluation.py
+++ b/pytorch_lightning/utilities/evaluation.py
@@ -1,5 +1,6 @@
 import torch
 
+
 def get_loss(model, X, y, criterion):
     preds = model(X)
     loss = criterion(preds, y)

From d004722d07655ea69304eec771695159975c8a1d Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Wed, 6 Oct 2021 23:44:34 +0530
Subject: [PATCH 09/53] Create evaluation.py

---
 pytorch_lightning/utilities/evaluation.py | 39 +++++++++++++++++------
 1 file changed, 30 insertions(+), 9 deletions(-)

diff --git a/pytorch_lightning/utilities/evaluation.py b/pytorch_lightning/utilities/evaluation.py
index cb029a82f2681..9b35ff2f41fda 100644
--- a/pytorch_lightning/utilities/evaluation.py
+++ b/pytorch_lightning/utilities/evaluation.py
@@ -1,19 +1,40 @@
 import torch
 
-
-def get_loss(model, X, y, criterion):
-    preds = model(X)
-    loss = criterion(preds, y)
+def get_loss(model, X, y, criterion,device='cpu',model_eval=False) -> float:
+    """
+    model:
+    """
+    if model_eval is True: # Check is model_eval is True
+        model.eval() # If model_eval is true this funtion will turn the model's state to evaluation.
+    else: 
+        model.train() # If model_eval is false this funtion will turn the model's state to train
+    model.to(device)
+    X = X.to(device)
+    y = y.to(device)
+    preds = model(X) # Predicting X
+    loss = criterion(preds, y) # Calculating loss
     return loss.item()
 
 
-def get_accuracy(model, X, y):
-    preds = model(X)
+def get_accuracy(model, X, y,device:str='cpu',model_eval:bool=False,argmax:bool=False) -> float:
+    if model_eval is True: # Check is model_eval is True
+        model.eval() # If model_eval is true this funtion will turn the model's state to evaluation.
+    else:
+        model.train() # If model_eval is false this funtion will turn the model's state to train
+    model.to(device)
+    X = X.to(device)
+    y = y.to(device)
+    preds = model(X) # Predicting X
+    preds = preds.to(device) # Convert predictions to the device
     correct = 0
     total = 0
-    for pred, yb in zip(preds, y):
-        pred = int(torch.argmax(pred))
-        yb = int(torch.argmax(yb))
+    for pred, yb in zip(preds, y): # iterating over the predictions and the truth
+        if argmax: # check if the pred and the truth is like [0,1,0] [1,0,0]
+            pred = int(torch.argmax(pred))
+            yb = int(torch.argmax(yb))
+        else: # checking if the pred and the truth is like 1 5
+            pred = int(torch.round(pred))
+            yb = int(torch.round(yb))
         if pred == yb:
             correct += 1
         total += 1

From 741bec7636397141dc581c10e04f712d26010178 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Wed, 6 Oct 2021 18:15:43 +0000
Subject: [PATCH 10/53] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 pytorch_lightning/utilities/evaluation.py | 33 ++++++++++++-----------
 1 file changed, 17 insertions(+), 16 deletions(-)

diff --git a/pytorch_lightning/utilities/evaluation.py b/pytorch_lightning/utilities/evaluation.py
index 9b35ff2f41fda..dbf59681c16f0 100644
--- a/pytorch_lightning/utilities/evaluation.py
+++ b/pytorch_lightning/utilities/evaluation.py
@@ -1,38 +1,39 @@
 import torch
 
-def get_loss(model, X, y, criterion,device='cpu',model_eval=False) -> float:
+
+def get_loss(model, X, y, criterion, device="cpu", model_eval=False) -> float:
     """
     model:
     """
-    if model_eval is True: # Check is model_eval is True
-        model.eval() # If model_eval is true this funtion will turn the model's state to evaluation.
-    else: 
-        model.train() # If model_eval is false this funtion will turn the model's state to train
+    if model_eval is True:  # Check is model_eval is True
+        model.eval()  # If model_eval is true this funtion will turn the model's state to evaluation.
+    else:
+        model.train()  # If model_eval is false this funtion will turn the model's state to train
     model.to(device)
     X = X.to(device)
     y = y.to(device)
-    preds = model(X) # Predicting X
-    loss = criterion(preds, y) # Calculating loss
+    preds = model(X)  # Predicting X
+    loss = criterion(preds, y)  # Calculating loss
     return loss.item()
 
 
-def get_accuracy(model, X, y,device:str='cpu',model_eval:bool=False,argmax:bool=False) -> float:
-    if model_eval is True: # Check is model_eval is True
-        model.eval() # If model_eval is true this funtion will turn the model's state to evaluation.
+def get_accuracy(model, X, y, device: str = "cpu", model_eval: bool = False, argmax: bool = False) -> float:
+    if model_eval is True:  # Check is model_eval is True
+        model.eval()  # If model_eval is true this funtion will turn the model's state to evaluation.
     else:
-        model.train() # If model_eval is false this funtion will turn the model's state to train
+        model.train()  # If model_eval is false this funtion will turn the model's state to train
     model.to(device)
     X = X.to(device)
     y = y.to(device)
-    preds = model(X) # Predicting X
-    preds = preds.to(device) # Convert predictions to the device
+    preds = model(X)  # Predicting X
+    preds = preds.to(device)  # Convert predictions to the device
     correct = 0
     total = 0
-    for pred, yb in zip(preds, y): # iterating over the predictions and the truth
-        if argmax: # check if the pred and the truth is like [0,1,0] [1,0,0]
+    for pred, yb in zip(preds, y):  # iterating over the predictions and the truth
+        if argmax:  # check if the pred and the truth is like [0,1,0] [1,0,0]
             pred = int(torch.argmax(pred))
             yb = int(torch.argmax(yb))
-        else: # checking if the pred and the truth is like 1 5
+        else:  # checking if the pred and the truth is like 1 5
             pred = int(torch.round(pred))
             yb = int(torch.round(yb))
         if pred == yb:

From 725b1ccf9d3f63c7ff237e6f52041186f93b93cd Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Wed, 6 Oct 2021 23:47:48 +0530
Subject: [PATCH 11/53] Create evaluation.py

---
 pytorch_lightning/utilities/evaluation.py | 47 +++++++++++++++--------
 1 file changed, 30 insertions(+), 17 deletions(-)

diff --git a/pytorch_lightning/utilities/evaluation.py b/pytorch_lightning/utilities/evaluation.py
index dbf59681c16f0..f39f6f0b78521 100644
--- a/pytorch_lightning/utilities/evaluation.py
+++ b/pytorch_lightning/utilities/evaluation.py
@@ -1,39 +1,52 @@
 import torch
 
-
-def get_loss(model, X, y, criterion, device="cpu", model_eval=False) -> float:
+def get_loss(model, X, y, criterion,device='cpu',model_eval=False) -> float:
     """
     model:
+    X:Inputs of the Model
+    y:Ground Truths
+    criterion:
+    device:the device that the model and all of the operations are run on
+    model_eval:should this funtion convert the model to a train state or eval state
     """
-    if model_eval is True:  # Check is model_eval is True
-        model.eval()  # If model_eval is true this funtion will turn the model's state to evaluation.
-    else:
-        model.train()  # If model_eval is false this funtion will turn the model's state to train
+    if model_eval is True: # Check is model_eval is True
+        model.eval() # If model_eval is true this funtion will turn the model's state to evaluation.
+    else: 
+        model.train() # If model_eval is false this funtion will turn the model's state to train
     model.to(device)
     X = X.to(device)
     y = y.to(device)
-    preds = model(X)  # Predicting X
-    loss = criterion(preds, y)  # Calculating loss
+    preds = model(X) # Predicting X
+    loss = criterion(preds, y) # Calculating loss
     return loss.item()
 
 
-def get_accuracy(model, X, y, device: str = "cpu", model_eval: bool = False, argmax: bool = False) -> float:
-    if model_eval is True:  # Check is model_eval is True
-        model.eval()  # If model_eval is true this funtion will turn the model's state to evaluation.
+def get_accuracy(model, X, y,device:str='cpu',model_eval:bool=False,argmax:bool=False) -> float:
+    """
+    model:
+    X:Inputs of the Model
+    y:Ground Truths
+    criterion:
+    device:the device that the model and all of the operations are run on
+    model_eval:should this funtion convert the model to a train state or eval state
+    argmax:True - check if the pred and the truth is like [0,1,0] [1,0,0] False - checking if the pred and the truth is like 1 5
+    """
+    if model_eval is True: # Check is model_eval is True
+        model.eval() # If model_eval is true this funtion will turn the model's state to evaluation.
     else:
-        model.train()  # If model_eval is false this funtion will turn the model's state to train
+        model.train() # If model_eval is false this funtion will turn the model's state to train
     model.to(device)
     X = X.to(device)
     y = y.to(device)
-    preds = model(X)  # Predicting X
-    preds = preds.to(device)  # Convert predictions to the device
+    preds = model(X) # Predicting X
+    preds = preds.to(device) # Convert predictions to the device
     correct = 0
     total = 0
-    for pred, yb in zip(preds, y):  # iterating over the predictions and the truth
-        if argmax:  # check if the pred and the truth is like [0,1,0] [1,0,0]
+    for pred, yb in zip(preds, y): # iterating over the predictions and the truth
+        if argmax: # check if the pred and the truth is like [0,1,0] [1,0,0]
             pred = int(torch.argmax(pred))
             yb = int(torch.argmax(yb))
-        else:  # checking if the pred and the truth is like 1 5
+        else: # checking if the pred and the truth is like 1 5
             pred = int(torch.round(pred))
             yb = int(torch.round(yb))
         if pred == yb:

From 646c929201c85e398a4707a247b68618025658b9 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Wed, 6 Oct 2021 18:18:57 +0000
Subject: [PATCH 12/53] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 pytorch_lightning/utilities/evaluation.py | 33 ++++++++++++-----------
 1 file changed, 17 insertions(+), 16 deletions(-)

diff --git a/pytorch_lightning/utilities/evaluation.py b/pytorch_lightning/utilities/evaluation.py
index f39f6f0b78521..25b1a65cf7679 100644
--- a/pytorch_lightning/utilities/evaluation.py
+++ b/pytorch_lightning/utilities/evaluation.py
@@ -1,6 +1,7 @@
 import torch
 
-def get_loss(model, X, y, criterion,device='cpu',model_eval=False) -> float:
+
+def get_loss(model, X, y, criterion, device="cpu", model_eval=False) -> float:
     """
     model:
     X:Inputs of the Model
@@ -9,19 +10,19 @@ def get_loss(model, X, y, criterion,device='cpu',model_eval=False) -> float:
     device:the device that the model and all of the operations are run on
     model_eval:should this funtion convert the model to a train state or eval state
     """
-    if model_eval is True: # Check is model_eval is True
-        model.eval() # If model_eval is true this funtion will turn the model's state to evaluation.
-    else: 
-        model.train() # If model_eval is false this funtion will turn the model's state to train
+    if model_eval is True:  # Check is model_eval is True
+        model.eval()  # If model_eval is true this funtion will turn the model's state to evaluation.
+    else:
+        model.train()  # If model_eval is false this funtion will turn the model's state to train
     model.to(device)
     X = X.to(device)
     y = y.to(device)
-    preds = model(X) # Predicting X
-    loss = criterion(preds, y) # Calculating loss
+    preds = model(X)  # Predicting X
+    loss = criterion(preds, y)  # Calculating loss
     return loss.item()
 
 
-def get_accuracy(model, X, y,device:str='cpu',model_eval:bool=False,argmax:bool=False) -> float:
+def get_accuracy(model, X, y, device: str = "cpu", model_eval: bool = False, argmax: bool = False) -> float:
     """
     model:
     X:Inputs of the Model
@@ -31,22 +32,22 @@ def get_accuracy(model, X, y,device:str='cpu',model_eval:bool=False,argmax:bool=
     model_eval:should this funtion convert the model to a train state or eval state
     argmax:True - check if the pred and the truth is like [0,1,0] [1,0,0] False - checking if the pred and the truth is like 1 5
     """
-    if model_eval is True: # Check is model_eval is True
-        model.eval() # If model_eval is true this funtion will turn the model's state to evaluation.
+    if model_eval is True:  # Check is model_eval is True
+        model.eval()  # If model_eval is true this funtion will turn the model's state to evaluation.
     else:
-        model.train() # If model_eval is false this funtion will turn the model's state to train
+        model.train()  # If model_eval is false this funtion will turn the model's state to train
     model.to(device)
     X = X.to(device)
     y = y.to(device)
-    preds = model(X) # Predicting X
-    preds = preds.to(device) # Convert predictions to the device
+    preds = model(X)  # Predicting X
+    preds = preds.to(device)  # Convert predictions to the device
     correct = 0
     total = 0
-    for pred, yb in zip(preds, y): # iterating over the predictions and the truth
-        if argmax: # check if the pred and the truth is like [0,1,0] [1,0,0]
+    for pred, yb in zip(preds, y):  # iterating over the predictions and the truth
+        if argmax:  # check if the pred and the truth is like [0,1,0] [1,0,0]
             pred = int(torch.argmax(pred))
             yb = int(torch.argmax(yb))
-        else: # checking if the pred and the truth is like 1 5
+        else:  # checking if the pred and the truth is like 1 5
             pred = int(torch.round(pred))
             yb = int(torch.round(yb))
         if pred == yb:

From 8f4916c166531ef7ba765dbe5e4e74ea76cd8848 Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Thu, 7 Oct 2021 08:22:56 +0530
Subject: [PATCH 13/53] Update evaluation.py

---
 pytorch_lightning/utilities/evaluation.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pytorch_lightning/utilities/evaluation.py b/pytorch_lightning/utilities/evaluation.py
index 25b1a65cf7679..47b4cae29006a 100644
--- a/pytorch_lightning/utilities/evaluation.py
+++ b/pytorch_lightning/utilities/evaluation.py
@@ -30,7 +30,7 @@ def get_accuracy(model, X, y, device: str = "cpu", model_eval: bool = False, arg
     criterion:
     device:the device that the model and all of the operations are run on
     model_eval:should this funtion convert the model to a train state or eval state
-    argmax:True - check if the pred and the truth is like [0,1,0] [1,0,0] False - checking if the pred and the truth is like 1 5
+    argmax:True - [0,1,0] [1,0,0] False -1 5
     """
     if model_eval is True:  # Check is model_eval is True
         model.eval()  # If model_eval is true this funtion will turn the model's state to evaluation.

From 543195c9e1cc1c3a6b7885444ffef10dfa68621e Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Thu, 7 Oct 2021 08:58:11 +0530
Subject: [PATCH 14/53] Create nlp.py

---
 pytorch_lightning/utilities/nlp.py | 62 ++++++++++++++++++++++++++++++
 1 file changed, 62 insertions(+)
 create mode 100644 pytorch_lightning/utilities/nlp.py

diff --git a/pytorch_lightning/utilities/nlp.py b/pytorch_lightning/utilities/nlp.py
new file mode 100644
index 0000000000000..95d5bd303dfcb
--- /dev/null
+++ b/pytorch_lightning/utilities/nlp.py
@@ -0,0 +1,62 @@
+import numpy as np
+import nltk
+from nltk.stem.porter import PorterStemmer
+from sklearn.model_selection import train_test_split
+import torch
+from tqdm import tqdm
+stemmer = PorterStemmer()
+
+def tokenize(sentence):
+  return nltk.word_tokenize(sentence)
+
+def stem(word):
+  return stemmmer.stem(word.lower())
+
+def bag_of_words(tokenized_words,all_words):
+  tokenized_words =  [stem(w) for w in tokenized_words]
+  bag = np.zeros(len(all_words))
+  for idx,w in enumerate(all_words):
+    if w in tokenized_words:
+      bag[idx] = 1.0
+  return bag
+
+def create_nlp_data(X,y,matrix_y:bool=False,device:str='cpu',test_size:float=0.25):
+  data = []
+  labels = {}
+  labels_r = {}
+  idx = 0
+  words = []
+  for label in y:
+    if label not in list(labels.keys()):
+      idx += 1
+      labels[label] = 1
+  for X_batch,y_batch in tqdm(zip(X,y)):
+    X_batch = tokenize(X_batch)
+    new_X = []
+    for Xb in X_batch:
+        new_X.append(stem(Xb))
+    words.extend(new_X)
+    if matrix_y is True:
+      data.append([
+          new_X,
+          np.eye(labels[y_batch],len(labels))[labels[y_batch]-1]
+      ])
+    else:
+      data.append([
+        new_X,
+        labels[y_batch]
+      ])
+  words = sorted(set(words))
+  np.random.shuffle(words)
+  np.random.shuffle(data)
+  X = []
+  y = []
+  for sentence,tag in tqdm(data):
+      X.append(bag_of_words(sentence,words))
+      y.append(tag)
+  X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=test_size,shuffle=False) 
+  X_train = torch.from_numpy(np.array(X_train)).to(device).float()
+  y_train = torch.from_numpy(np.array(y_train)).to(device).float()  
+  X_test = torch.from_numpy(np.array(X_test)).to(device).float()
+  y_test = torch.from_numpy(np.array(y_test)).to(device).float()
+  return X_train,X_test,y_train,y_test,X,y,data,words,labels,labels_r

From c08ed599a334407fd1707404005e7420b806e359 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Thu, 7 Oct 2021 03:29:20 +0000
Subject: [PATCH 15/53] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 pytorch_lightning/utilities/nlp.py | 105 ++++++++++++++---------------
 1 file changed, 52 insertions(+), 53 deletions(-)

diff --git a/pytorch_lightning/utilities/nlp.py b/pytorch_lightning/utilities/nlp.py
index 95d5bd303dfcb..a4e1510c9b7de 100644
--- a/pytorch_lightning/utilities/nlp.py
+++ b/pytorch_lightning/utilities/nlp.py
@@ -1,62 +1,61 @@
-import numpy as np
 import nltk
+import numpy as np
+import torch
 from nltk.stem.porter import PorterStemmer
 from sklearn.model_selection import train_test_split
-import torch
 from tqdm import tqdm
+
 stemmer = PorterStemmer()
 
+
 def tokenize(sentence):
-  return nltk.word_tokenize(sentence)
+    return nltk.word_tokenize(sentence)
+
 
 def stem(word):
-  return stemmmer.stem(word.lower())
-
-def bag_of_words(tokenized_words,all_words):
-  tokenized_words =  [stem(w) for w in tokenized_words]
-  bag = np.zeros(len(all_words))
-  for idx,w in enumerate(all_words):
-    if w in tokenized_words:
-      bag[idx] = 1.0
-  return bag
-
-def create_nlp_data(X,y,matrix_y:bool=False,device:str='cpu',test_size:float=0.25):
-  data = []
-  labels = {}
-  labels_r = {}
-  idx = 0
-  words = []
-  for label in y:
-    if label not in list(labels.keys()):
-      idx += 1
-      labels[label] = 1
-  for X_batch,y_batch in tqdm(zip(X,y)):
-    X_batch = tokenize(X_batch)
-    new_X = []
-    for Xb in X_batch:
-        new_X.append(stem(Xb))
-    words.extend(new_X)
-    if matrix_y is True:
-      data.append([
-          new_X,
-          np.eye(labels[y_batch],len(labels))[labels[y_batch]-1]
-      ])
-    else:
-      data.append([
-        new_X,
-        labels[y_batch]
-      ])
-  words = sorted(set(words))
-  np.random.shuffle(words)
-  np.random.shuffle(data)
-  X = []
-  y = []
-  for sentence,tag in tqdm(data):
-      X.append(bag_of_words(sentence,words))
-      y.append(tag)
-  X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=test_size,shuffle=False) 
-  X_train = torch.from_numpy(np.array(X_train)).to(device).float()
-  y_train = torch.from_numpy(np.array(y_train)).to(device).float()  
-  X_test = torch.from_numpy(np.array(X_test)).to(device).float()
-  y_test = torch.from_numpy(np.array(y_test)).to(device).float()
-  return X_train,X_test,y_train,y_test,X,y,data,words,labels,labels_r
+    return stemmmer.stem(word.lower())
+
+
+def bag_of_words(tokenized_words, all_words):
+    tokenized_words = [stem(w) for w in tokenized_words]
+    bag = np.zeros(len(all_words))
+    for idx, w in enumerate(all_words):
+        if w in tokenized_words:
+            bag[idx] = 1.0
+    return bag
+
+
+def create_nlp_data(X, y, matrix_y: bool = False, device: str = "cpu", test_size: float = 0.25):
+    data = []
+    labels = {}
+    labels_r = {}
+    idx = 0
+    words = []
+    for label in y:
+        if label not in list(labels.keys()):
+            idx += 1
+            labels[label] = 1
+    for X_batch, y_batch in tqdm(zip(X, y)):
+        X_batch = tokenize(X_batch)
+        new_X = []
+        for Xb in X_batch:
+            new_X.append(stem(Xb))
+        words.extend(new_X)
+        if matrix_y is True:
+            data.append([new_X, np.eye(labels[y_batch], len(labels))[labels[y_batch] - 1]])
+        else:
+            data.append([new_X, labels[y_batch]])
+    words = sorted(set(words))
+    np.random.shuffle(words)
+    np.random.shuffle(data)
+    X = []
+    y = []
+    for sentence, tag in tqdm(data):
+        X.append(bag_of_words(sentence, words))
+        y.append(tag)
+    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_size, shuffle=False)
+    X_train = torch.from_numpy(np.array(X_train)).to(device).float()
+    y_train = torch.from_numpy(np.array(y_train)).to(device).float()
+    X_test = torch.from_numpy(np.array(X_test)).to(device).float()
+    y_test = torch.from_numpy(np.array(y_test)).to(device).float()
+    return X_train, X_test, y_train, y_test, X, y, data, words, labels, labels_r

From d22b3a48cbe35c5e58bf9a47f358f8fa789c8b15 Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Thu, 7 Oct 2021 09:04:16 +0530
Subject: [PATCH 16/53] Update evaluation.py

---
 pytorch_lightning/utilities/evaluation.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pytorch_lightning/utilities/evaluation.py b/pytorch_lightning/utilities/evaluation.py
index 47b4cae29006a..ab39fd6239582 100644
--- a/pytorch_lightning/utilities/evaluation.py
+++ b/pytorch_lightning/utilities/evaluation.py
@@ -29,7 +29,7 @@ def get_accuracy(model, X, y, device: str = "cpu", model_eval: bool = False, arg
     y:Ground Truths
     criterion:
     device:the device that the model and all of the operations are run on
-    model_eval:should this funtion convert the model to a train state or eval state
+    model_eval:convert the model to a train state or eval state
     argmax:True - [0,1,0] [1,0,0] False -1 5
     """
     if model_eval is True:  # Check is model_eval is True

From 992023d883520c105e5b788f5c423e4789d3d499 Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Thu, 7 Oct 2021 09:07:07 +0530
Subject: [PATCH 17/53] Create evaluation.py

---
 pytorch_lightning/utilities/evaluation.py | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/pytorch_lightning/utilities/evaluation.py b/pytorch_lightning/utilities/evaluation.py
index ab39fd6239582..cc844e9e5ec33 100644
--- a/pytorch_lightning/utilities/evaluation.py
+++ b/pytorch_lightning/utilities/evaluation.py
@@ -11,9 +11,9 @@ def get_loss(model, X, y, criterion, device="cpu", model_eval=False) -> float:
     model_eval:should this funtion convert the model to a train state or eval state
     """
     if model_eval is True:  # Check is model_eval is True
-        model.eval()  # If model_eval is true this funtion will turn the model's state to evaluation.
+        model.eval()
     else:
-        model.train()  # If model_eval is false this funtion will turn the model's state to train
+        model.train()
     model.to(device)
     X = X.to(device)
     y = y.to(device)
@@ -28,14 +28,14 @@ def get_accuracy(model, X, y, device: str = "cpu", model_eval: bool = False, arg
     X:Inputs of the Model
     y:Ground Truths
     criterion:
-    device:the device that the model and all of the operations are run on
+    device:the device that all of the operations are run on
     model_eval:convert the model to a train state or eval state
     argmax:True - [0,1,0] [1,0,0] False -1 5
     """
     if model_eval is True:  # Check is model_eval is True
-        model.eval()  # If model_eval is true this funtion will turn the model's state to evaluation.
+        model.eval()
     else:
-        model.train()  # If model_eval is false this funtion will turn the model's state to train
+        model.train()
     model.to(device)
     X = X.to(device)
     y = y.to(device)

From 28a767044f2d7b11eb248d8fde89f11995fed9c9 Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Thu, 7 Oct 2021 09:09:33 +0530
Subject: [PATCH 18/53] Update nlp.py

---
 pytorch_lightning/utilities/nlp.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pytorch_lightning/utilities/nlp.py b/pytorch_lightning/utilities/nlp.py
index a4e1510c9b7de..3e8e91a8399da 100644
--- a/pytorch_lightning/utilities/nlp.py
+++ b/pytorch_lightning/utilities/nlp.py
@@ -13,7 +13,7 @@ def tokenize(sentence):
 
 
 def stem(word):
-    return stemmmer.stem(word.lower())
+    return stemmer.stem(word.lower())
 
 
 def bag_of_words(tokenized_words, all_words):

From 4751e2774f09a6c26012a67da0551a822e4af0d5 Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Thu, 7 Oct 2021 09:42:15 +0530
Subject: [PATCH 19/53] Update nlp.py

---
 pytorch_lightning/utilities/nlp.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pytorch_lightning/utilities/nlp.py b/pytorch_lightning/utilities/nlp.py
index 3e8e91a8399da..23feceda08b07 100644
--- a/pytorch_lightning/utilities/nlp.py
+++ b/pytorch_lightning/utilities/nlp.py
@@ -25,7 +25,7 @@ def bag_of_words(tokenized_words, all_words):
     return bag
 
 
-def create_nlp_data(X, y, matrix_y: bool = False, device: str = "cpu", test_size: float = 0.25):
+def create_nlp_data(X, y, matrix_y: bool = False, device: str, test_size: float = 0.25):
     data = []
     labels = {}
     labels_r = {}

From f7272074eb8b164553197fe791c8e2716e2a4000 Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Thu, 7 Oct 2021 09:42:17 +0530
Subject: [PATCH 20/53] Update evaluation.py

---
 pytorch_lightning/utilities/evaluation.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/pytorch_lightning/utilities/evaluation.py b/pytorch_lightning/utilities/evaluation.py
index cc844e9e5ec33..e152daf6f0b2a 100644
--- a/pytorch_lightning/utilities/evaluation.py
+++ b/pytorch_lightning/utilities/evaluation.py
@@ -1,7 +1,7 @@
 import torch
 
 
-def get_loss(model, X, y, criterion, device="cpu", model_eval=False) -> float:
+def get_loss(model, X, y, criterion, device, model_eval=False) -> float:
     """
     model:
     X:Inputs of the Model
@@ -22,7 +22,7 @@ def get_loss(model, X, y, criterion, device="cpu", model_eval=False) -> float:
     return loss.item()
 
 
-def get_accuracy(model, X, y, device: str = "cpu", model_eval: bool = False, argmax: bool = False) -> float:
+def get_accuracy(model, X, y, device: str, model_eval: bool = False, argmax: bool = False) -> float:
     """
     model:
     X:Inputs of the Model

From e3a3acc56fe32967ff432e1914ee7ed4795cfa0b Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Thu, 7 Oct 2021 09:42:23 +0530
Subject: [PATCH 21/53] Create evaluation.py


From c410db0a2ec07e3e889068e4d9fbf46c0f99f78f Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Thu, 7 Oct 2021 10:29:06 +0530
Subject: [PATCH 22/53] Update nlp.py

---
 pytorch_lightning/utilities/nlp.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pytorch_lightning/utilities/nlp.py b/pytorch_lightning/utilities/nlp.py
index 23feceda08b07..8122c7c1510fd 100644
--- a/pytorch_lightning/utilities/nlp.py
+++ b/pytorch_lightning/utilities/nlp.py
@@ -25,7 +25,7 @@ def bag_of_words(tokenized_words, all_words):
     return bag
 
 
-def create_nlp_data(X, y, matrix_y: bool = False, device: str, test_size: float = 0.25):
+def create_nlp_data(X, y, device: str, matrix_y: bool = False, test_size: float = 0.25):
     data = []
     labels = {}
     labels_r = {}

From 03a5dcc1d2f456ae7f1c7a69a7baaf6ae320409f Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Thu, 7 Oct 2021 10:31:49 +0530
Subject: [PATCH 23/53] Update nlp.py

---
 pytorch_lightning/utilities/nlp.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

diff --git a/pytorch_lightning/utilities/nlp.py b/pytorch_lightning/utilities/nlp.py
index 8122c7c1510fd..4c42ada8fa393 100644
--- a/pytorch_lightning/utilities/nlp.py
+++ b/pytorch_lightning/utilities/nlp.py
@@ -8,11 +8,11 @@
 stemmer = PorterStemmer()
 
 
-def tokenize(sentence):
+def tokenize(sentence) -> list:
     return nltk.word_tokenize(sentence)
 
 
-def stem(word):
+def stem(word) -> str:
     return stemmer.stem(word.lower())
 
 
@@ -25,7 +25,7 @@ def bag_of_words(tokenized_words, all_words):
     return bag
 
 
-def create_nlp_data(X, y, device: str, matrix_y: bool = False, test_size: float = 0.25):
+def create_nlp_data(X, y, device: str, matrix_y: bool = False, test_size: float = 0.25) -> 'X_train, X_test, y_train, y_test, X, y, data, words, labels, labels_r':
     data = []
     labels = {}
     labels_r = {}

From e053747cb9600fdecf304d32e05da453220a7a92 Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Thu, 7 Oct 2021 10:32:57 +0530
Subject: [PATCH 24/53] Update requirements.txt

---
 requirements.txt | 1 +
 1 file changed, 1 insertion(+)

diff --git a/requirements.txt b/requirements.txt
index 2b0f7c04f19f8..d485c23094603 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -8,6 +8,7 @@ PyYAML>=5.1
 fsspec[http]>=2021.05.0, !=2021.06.0
 tensorboard>=2.2.0
 torchmetrics>=0.4.1
+nltk>=3.6.3
 pyDeprecate==0.3.1
 packaging>=17.0
 typing-extensions  # TypedDict support for python<3.8

From 267085a68f5e3acb713f14618822f8511ae38661 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Thu, 7 Oct 2021 05:02:58 +0000
Subject: [PATCH 25/53] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 pytorch_lightning/utilities/nlp.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/pytorch_lightning/utilities/nlp.py b/pytorch_lightning/utilities/nlp.py
index 4c42ada8fa393..9c3bf838942af 100644
--- a/pytorch_lightning/utilities/nlp.py
+++ b/pytorch_lightning/utilities/nlp.py
@@ -25,7 +25,9 @@ def bag_of_words(tokenized_words, all_words):
     return bag
 
 
-def create_nlp_data(X, y, device: str, matrix_y: bool = False, test_size: float = 0.25) -> 'X_train, X_test, y_train, y_test, X, y, data, words, labels, labels_r':
+def create_nlp_data(
+    X, y, device: str, matrix_y: bool = False, test_size: float = 0.25
+) -> "X_train, X_test, y_train, y_test, X, y, data, words, labels, labels_r":
     data = []
     labels = {}
     labels_r = {}

From 78528a0f5b75fbfb0d2c95921f7867bdc6af72ee Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Thu, 7 Oct 2021 10:39:36 +0530
Subject: [PATCH 26/53] Update evaluation.py

---
 pytorch_lightning/utilities/evaluation.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/pytorch_lightning/utilities/evaluation.py b/pytorch_lightning/utilities/evaluation.py
index e152daf6f0b2a..5ffce1e15cf5e 100644
--- a/pytorch_lightning/utilities/evaluation.py
+++ b/pytorch_lightning/utilities/evaluation.py
@@ -30,6 +30,7 @@ def get_accuracy(model, X, y, device: str, model_eval: bool = False, argmax: boo
     criterion:
     device:the device that all of the operations are run on
     model_eval:convert the model to a train state or eval state
+    
     argmax:True - [0,1,0] [1,0,0] False -1 5
     """
     if model_eval is True:  # Check is model_eval is True

From 851009700f62a5b3169813ef4e73c73861beea1d Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Thu, 7 Oct 2021 05:10:45 +0000
Subject: [PATCH 27/53] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 pytorch_lightning/utilities/evaluation.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pytorch_lightning/utilities/evaluation.py b/pytorch_lightning/utilities/evaluation.py
index 5ffce1e15cf5e..c30fc05c6dca2 100644
--- a/pytorch_lightning/utilities/evaluation.py
+++ b/pytorch_lightning/utilities/evaluation.py
@@ -30,7 +30,7 @@ def get_accuracy(model, X, y, device: str, model_eval: bool = False, argmax: boo
     criterion:
     device:the device that all of the operations are run on
     model_eval:convert the model to a train state or eval state
-    
+
     argmax:True - [0,1,0] [1,0,0] False -1 5
     """
     if model_eval is True:  # Check is model_eval is True

From 3981c0fabf0f1dcbd4952375626b710e92eb710b Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Thu, 7 Oct 2021 17:01:01 +0530
Subject: [PATCH 28/53] Create data_loader.py

---
 pytorch_lightning/utilities/data_loader.py | 51 ++++++++++++++++++++++
 1 file changed, 51 insertions(+)
 create mode 100644 pytorch_lightning/utilities/data_loader.py

diff --git a/pytorch_lightning/utilities/data_loader.py b/pytorch_lightning/utilities/data_loader.py
new file mode 100644
index 0000000000000..db9e6f9f7279e
--- /dev/null
+++ b/pytorch_lightning/utilities/data_loader.py
@@ -0,0 +1,51 @@
+import os,cv2
+import numpy as np
+import torch,torchvision
+from tqdm import tqdm
+
+def load_data(data_dir:str,matrix:bool=False,idx_clf:bool=False):
+    """
+    data_dir : data_dir is the directory that you want to load the data from
+    matrix : if you want y as [0,1,0]
+    idx_clf : if you want y as 1 or 2 or 3
+    """
+    data = []
+    labels = {}
+    labels_r = {}
+    idx = 0
+    if matrix:
+      for label in os.listdir(data_dir):
+          idx += 1
+          labels[label] = idx
+          labels_r[idx] = label
+      for folder in os.listdir(data_dir):
+          for file in os.listdir(f'{data_dir}{folder}/'):
+              img = cv2.imread(f'{data_dir}{folder}/{file}')
+              img = cv2.resize(img,(56,56))
+              img = img / 255.0
+              data.append([
+                  img,
+                  np.eye(labels[folder]+1,len(labels))[labels[folder]-1]
+              ])
+      X = []
+      y = []
+      for d in data:
+          X.append(d[0])
+          y.append(d[1])
+    if idx_clf:
+      for folder in os.listdir(data_dir):
+          idx += 1
+          for file in os.listdir(f'{data_dir}{folder}/'):
+              img = cv2.imread(f'{data_dir}{folder}/{file}')
+              img = cv2.resize(img,(56,56))
+              img = img / 255.0
+              data.append([
+                  img,
+                  idx
+              ])
+      X = []
+      y = []
+      for d in data:
+          X.append(d[0])
+          y.append(d[1])
+    return X,y,labels,labels_r,idx,data

From 577e7465c60fdeadd11c85892fca0cc001ee84d4 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Thu, 7 Oct 2021 11:32:35 +0000
Subject: [PATCH 29/53] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 pytorch_lightning/utilities/data_loader.py | 72 +++++++++++-----------
 1 file changed, 35 insertions(+), 37 deletions(-)

diff --git a/pytorch_lightning/utilities/data_loader.py b/pytorch_lightning/utilities/data_loader.py
index db9e6f9f7279e..40af4e32a4058 100644
--- a/pytorch_lightning/utilities/data_loader.py
+++ b/pytorch_lightning/utilities/data_loader.py
@@ -1,9 +1,13 @@
-import os,cv2
+import os
+
+import cv2
 import numpy as np
-import torch,torchvision
+import torch
+import torchvision
 from tqdm import tqdm
 
-def load_data(data_dir:str,matrix:bool=False,idx_clf:bool=False):
+
+def load_data(data_dir: str, matrix: bool = False, idx_clf: bool = False):
     """
     data_dir : data_dir is the directory that you want to load the data from
     matrix : if you want y as [0,1,0]
@@ -14,38 +18,32 @@ def load_data(data_dir:str,matrix:bool=False,idx_clf:bool=False):
     labels_r = {}
     idx = 0
     if matrix:
-      for label in os.listdir(data_dir):
-          idx += 1
-          labels[label] = idx
-          labels_r[idx] = label
-      for folder in os.listdir(data_dir):
-          for file in os.listdir(f'{data_dir}{folder}/'):
-              img = cv2.imread(f'{data_dir}{folder}/{file}')
-              img = cv2.resize(img,(56,56))
-              img = img / 255.0
-              data.append([
-                  img,
-                  np.eye(labels[folder]+1,len(labels))[labels[folder]-1]
-              ])
-      X = []
-      y = []
-      for d in data:
-          X.append(d[0])
-          y.append(d[1])
+        for label in os.listdir(data_dir):
+            idx += 1
+            labels[label] = idx
+            labels_r[idx] = label
+        for folder in os.listdir(data_dir):
+            for file in os.listdir(f"{data_dir}{folder}/"):
+                img = cv2.imread(f"{data_dir}{folder}/{file}")
+                img = cv2.resize(img, (56, 56))
+                img = img / 255.0
+                data.append([img, np.eye(labels[folder] + 1, len(labels))[labels[folder] - 1]])
+        X = []
+        y = []
+        for d in data:
+            X.append(d[0])
+            y.append(d[1])
     if idx_clf:
-      for folder in os.listdir(data_dir):
-          idx += 1
-          for file in os.listdir(f'{data_dir}{folder}/'):
-              img = cv2.imread(f'{data_dir}{folder}/{file}')
-              img = cv2.resize(img,(56,56))
-              img = img / 255.0
-              data.append([
-                  img,
-                  idx
-              ])
-      X = []
-      y = []
-      for d in data:
-          X.append(d[0])
-          y.append(d[1])
-    return X,y,labels,labels_r,idx,data
+        for folder in os.listdir(data_dir):
+            idx += 1
+            for file in os.listdir(f"{data_dir}{folder}/"):
+                img = cv2.imread(f"{data_dir}{folder}/{file}")
+                img = cv2.resize(img, (56, 56))
+                img = img / 255.0
+                data.append([img, idx])
+        X = []
+        y = []
+        for d in data:
+            X.append(d[0])
+            y.append(d[1])
+    return X, y, labels, labels_r, idx, data

From bf7315c47195b01d1cf0aa9b230ced66663e2312 Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Thu, 7 Oct 2021 17:17:34 +0530
Subject: [PATCH 30/53] Update nlp.py

---
 pytorch_lightning/utilities/nlp.py | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/pytorch_lightning/utilities/nlp.py b/pytorch_lightning/utilities/nlp.py
index 9c3bf838942af..868fde6615fda 100644
--- a/pytorch_lightning/utilities/nlp.py
+++ b/pytorch_lightning/utilities/nlp.py
@@ -26,7 +26,7 @@ def bag_of_words(tokenized_words, all_words):
 
 
 def create_nlp_data(
-    X, y, device: str, matrix_y: bool = False, test_size: float = 0.25
+    X, y, matrix_y: bool = False, test_size: float = 0.25
 ) -> "X_train, X_test, y_train, y_test, X, y, data, words, labels, labels_r":
     data = []
     labels = {}
@@ -56,8 +56,8 @@ def create_nlp_data(
         X.append(bag_of_words(sentence, words))
         y.append(tag)
     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_size, shuffle=False)
-    X_train = torch.from_numpy(np.array(X_train)).to(device).float()
-    y_train = torch.from_numpy(np.array(y_train)).to(device).float()
-    X_test = torch.from_numpy(np.array(X_test)).to(device).float()
-    y_test = torch.from_numpy(np.array(y_test)).to(device).float()
+    X_train = torch.from_numpy(np.array(X_train)).float()
+    y_train = torch.from_numpy(np.array(y_train)).float()
+    X_test = torch.from_numpy(np.array(X_test)).float()
+    y_test = torch.from_numpy(np.array(y_test)).float()
     return X_train, X_test, y_train, y_test, X, y, data, words, labels, labels_r

From 24fda2b53cc0e74a80f448c76369e59af2cfce22 Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Thu, 7 Oct 2021 17:18:10 +0530
Subject: [PATCH 31/53] Update evaluation.py

---
 pytorch_lightning/utilities/evaluation.py | 13 ++-----------
 1 file changed, 2 insertions(+), 11 deletions(-)

diff --git a/pytorch_lightning/utilities/evaluation.py b/pytorch_lightning/utilities/evaluation.py
index c30fc05c6dca2..ea3ed69134adf 100644
--- a/pytorch_lightning/utilities/evaluation.py
+++ b/pytorch_lightning/utilities/evaluation.py
@@ -1,34 +1,29 @@
 import torch
 
 
-def get_loss(model, X, y, criterion, device, model_eval=False) -> float:
+def get_loss(model, X, y, criterion, model_eval=False) -> float:
     """
     model:
     X:Inputs of the Model
     y:Ground Truths
     criterion:
-    device:the device that the model and all of the operations are run on
     model_eval:should this funtion convert the model to a train state or eval state
     """
     if model_eval is True:  # Check is model_eval is True
         model.eval()
     else:
         model.train()
-    model.to(device)
-    X = X.to(device)
-    y = y.to(device)
     preds = model(X)  # Predicting X
     loss = criterion(preds, y)  # Calculating loss
     return loss.item()
 
 
-def get_accuracy(model, X, y, device: str, model_eval: bool = False, argmax: bool = False) -> float:
+def get_accuracy(model, X, y, model_eval: bool = False, argmax: bool = False) -> float:
     """
     model:
     X:Inputs of the Model
     y:Ground Truths
     criterion:
-    device:the device that all of the operations are run on
     model_eval:convert the model to a train state or eval state
 
     argmax:True - [0,1,0] [1,0,0] False -1 5
@@ -37,11 +32,7 @@ def get_accuracy(model, X, y, device: str, model_eval: bool = False, argmax: boo
         model.eval()
     else:
         model.train()
-    model.to(device)
-    X = X.to(device)
-    y = y.to(device)
     preds = model(X)  # Predicting X
-    preds = preds.to(device)  # Convert predictions to the device
     correct = 0
     total = 0
     for pred, yb in zip(preds, y):  # iterating over the predictions and the truth

From e8323afa4739929b41006b6f18037445107737f0 Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Thu, 7 Oct 2021 18:21:26 +0530
Subject: [PATCH 32/53] Update data_loader.py

---
 pytorch_lightning/utilities/data_loader.py | 9 +++------
 1 file changed, 3 insertions(+), 6 deletions(-)

diff --git a/pytorch_lightning/utilities/data_loader.py b/pytorch_lightning/utilities/data_loader.py
index 40af4e32a4058..2a0354efe5f3f 100644
--- a/pytorch_lightning/utilities/data_loader.py
+++ b/pytorch_lightning/utilities/data_loader.py
@@ -1,9 +1,6 @@
 import os
-
 import cv2
 import numpy as np
-import torch
-import torchvision
 from tqdm import tqdm
 
 
@@ -22,15 +19,15 @@ def load_data(data_dir: str, matrix: bool = False, idx_clf: bool = False):
             idx += 1
             labels[label] = idx
             labels_r[idx] = label
-        for folder in os.listdir(data_dir):
-            for file in os.listdir(f"{data_dir}{folder}/"):
+        for folder in tqdm(os.listdir(data_dir)):
+            for file in tqdm(os.listdir(f"{data_dir}{folder}/")):
                 img = cv2.imread(f"{data_dir}{folder}/{file}")
                 img = cv2.resize(img, (56, 56))
                 img = img / 255.0
                 data.append([img, np.eye(labels[folder] + 1, len(labels))[labels[folder] - 1]])
         X = []
         y = []
-        for d in data:
+        for d in tqdm(data):
             X.append(d[0])
             y.append(d[1])
     if idx_clf:

From 713d6fa42e91002dbef634be40fccf3a2d47d4f2 Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Thu, 7 Oct 2021 18:21:28 +0530
Subject: [PATCH 33/53] Update nlp.py

---
 pytorch_lightning/utilities/nlp.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pytorch_lightning/utilities/nlp.py b/pytorch_lightning/utilities/nlp.py
index 868fde6615fda..3ab8e5a9681bd 100644
--- a/pytorch_lightning/utilities/nlp.py
+++ b/pytorch_lightning/utilities/nlp.py
@@ -27,7 +27,7 @@ def bag_of_words(tokenized_words, all_words):
 
 def create_nlp_data(
     X, y, matrix_y: bool = False, test_size: float = 0.25
-) -> "X_train, X_test, y_train, y_test, X, y, data, words, labels, labels_r":
+):
     data = []
     labels = {}
     labels_r = {}

From 5662aff801f509716a8546ddf285c77e6037f8bf Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Thu, 7 Oct 2021 12:52:36 +0000
Subject: [PATCH 34/53] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 pytorch_lightning/utilities/data_loader.py | 1 +
 pytorch_lightning/utilities/nlp.py         | 4 +---
 2 files changed, 2 insertions(+), 3 deletions(-)

diff --git a/pytorch_lightning/utilities/data_loader.py b/pytorch_lightning/utilities/data_loader.py
index 2a0354efe5f3f..b53f011c76e7e 100644
--- a/pytorch_lightning/utilities/data_loader.py
+++ b/pytorch_lightning/utilities/data_loader.py
@@ -1,4 +1,5 @@
 import os
+
 import cv2
 import numpy as np
 from tqdm import tqdm
diff --git a/pytorch_lightning/utilities/nlp.py b/pytorch_lightning/utilities/nlp.py
index 3ab8e5a9681bd..9ac33a429eb59 100644
--- a/pytorch_lightning/utilities/nlp.py
+++ b/pytorch_lightning/utilities/nlp.py
@@ -25,9 +25,7 @@ def bag_of_words(tokenized_words, all_words):
     return bag
 
 
-def create_nlp_data(
-    X, y, matrix_y: bool = False, test_size: float = 0.25
-):
+def create_nlp_data(X, y, matrix_y: bool = False, test_size: float = 0.25):
     data = []
     labels = {}
     labels_r = {}

From 7cf29781ef926a914387a9a21fecf6c536dacaa3 Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Thu, 7 Oct 2021 18:25:13 +0530
Subject: [PATCH 35/53] Update data_loader.py

---
 pytorch_lightning/utilities/data_loader.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/pytorch_lightning/utilities/data_loader.py b/pytorch_lightning/utilities/data_loader.py
index b53f011c76e7e..2a0354efe5f3f 100644
--- a/pytorch_lightning/utilities/data_loader.py
+++ b/pytorch_lightning/utilities/data_loader.py
@@ -1,5 +1,4 @@
 import os
-
 import cv2
 import numpy as np
 from tqdm import tqdm

From 618ac570739ba505ee515883cebaacd809df0c0d Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Thu, 7 Oct 2021 12:57:33 +0000
Subject: [PATCH 36/53] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 pytorch_lightning/utilities/data_loader.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/pytorch_lightning/utilities/data_loader.py b/pytorch_lightning/utilities/data_loader.py
index 2a0354efe5f3f..b53f011c76e7e 100644
--- a/pytorch_lightning/utilities/data_loader.py
+++ b/pytorch_lightning/utilities/data_loader.py
@@ -1,4 +1,5 @@
 import os
+
 import cv2
 import numpy as np
 from tqdm import tqdm

From c9563f9a11912ae61236df36c121946505b0e508 Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Fri, 8 Oct 2021 15:21:13 +0530
Subject: [PATCH 37/53] Update requirements.txt

---
 requirements.txt | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/requirements.txt b/requirements.txt
index d485c23094603..339847b13010a 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,14 +1,16 @@
 # the default package dependencies
 
 numpy>=1.17.2
-torch>=1.6
+torch>=1.8
 future>=0.17.1  # required for builtins in setup.py
 tqdm>=4.41.0
 PyYAML>=5.1
 fsspec[http]>=2021.05.0, !=2021.06.0
 tensorboard>=2.2.0
 torchmetrics>=0.4.1
+scikit-learn>=0.18.1
 nltk>=3.6.3
 pyDeprecate==0.3.1
 packaging>=17.0
 typing-extensions  # TypedDict support for python<3.8
+opencv-python>=4.5.3.56

From 20a97055aec8d1191bc9b6622269a231f8050931 Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Fri, 8 Oct 2021 16:20:43 +0530
Subject: [PATCH 38/53] Update model_checkpoint.py

---
 pytorch_lightning/callbacks/model_checkpoint.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/pytorch_lightning/callbacks/model_checkpoint.py b/pytorch_lightning/callbacks/model_checkpoint.py
index cff2116446b92..4ad9c0d70e2d7 100644
--- a/pytorch_lightning/callbacks/model_checkpoint.py
+++ b/pytorch_lightning/callbacks/model_checkpoint.py
@@ -222,6 +222,9 @@ def __init__(
         self.verbose = verbose
         self.save_last = save_last
         self.save_top_k = save_top_k
+        # TODO : The error is from #9868 do a better fix for the bug this is a solution for now
+        if self.save_top_k is None:
+            self.save_top_k = 0
         self.save_weights_only = save_weights_only
         self.auto_insert_metric_name = auto_insert_metric_name
         self._save_on_train_epoch_end = save_on_train_epoch_end

From 45f1373db89bbb0e69d23d57912248f3c140e903 Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Fri, 8 Oct 2021 17:08:15 +0530
Subject: [PATCH 39/53] Delete evaluation.py

---
 pytorch_lightning/utilities/evaluation.py | 49 -----------------------
 1 file changed, 49 deletions(-)
 delete mode 100644 pytorch_lightning/utilities/evaluation.py

diff --git a/pytorch_lightning/utilities/evaluation.py b/pytorch_lightning/utilities/evaluation.py
deleted file mode 100644
index ea3ed69134adf..0000000000000
--- a/pytorch_lightning/utilities/evaluation.py
+++ /dev/null
@@ -1,49 +0,0 @@
-import torch
-
-
-def get_loss(model, X, y, criterion, model_eval=False) -> float:
-    """
-    model:
-    X:Inputs of the Model
-    y:Ground Truths
-    criterion:
-    model_eval:should this funtion convert the model to a train state or eval state
-    """
-    if model_eval is True:  # Check is model_eval is True
-        model.eval()
-    else:
-        model.train()
-    preds = model(X)  # Predicting X
-    loss = criterion(preds, y)  # Calculating loss
-    return loss.item()
-
-
-def get_accuracy(model, X, y, model_eval: bool = False, argmax: bool = False) -> float:
-    """
-    model:
-    X:Inputs of the Model
-    y:Ground Truths
-    criterion:
-    model_eval:convert the model to a train state or eval state
-
-    argmax:True - [0,1,0] [1,0,0] False -1 5
-    """
-    if model_eval is True:  # Check is model_eval is True
-        model.eval()
-    else:
-        model.train()
-    preds = model(X)  # Predicting X
-    correct = 0
-    total = 0
-    for pred, yb in zip(preds, y):  # iterating over the predictions and the truth
-        if argmax:  # check if the pred and the truth is like [0,1,0] [1,0,0]
-            pred = int(torch.argmax(pred))
-            yb = int(torch.argmax(yb))
-        else:  # checking if the pred and the truth is like 1 5
-            pred = int(torch.round(pred))
-            yb = int(torch.round(yb))
-        if pred == yb:
-            correct += 1
-        total += 1
-    acc = round(correct / total, 3) * 100
-    return acc

From 7faf2ac7d169629933e6f82726f79840e5e72477 Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Fri, 8 Oct 2021 17:08:17 +0530
Subject: [PATCH 40/53] Delete data_loader.py

---
 pytorch_lightning/utilities/data_loader.py | 47 ----------------------
 1 file changed, 47 deletions(-)
 delete mode 100644 pytorch_lightning/utilities/data_loader.py

diff --git a/pytorch_lightning/utilities/data_loader.py b/pytorch_lightning/utilities/data_loader.py
deleted file mode 100644
index b53f011c76e7e..0000000000000
--- a/pytorch_lightning/utilities/data_loader.py
+++ /dev/null
@@ -1,47 +0,0 @@
-import os
-
-import cv2
-import numpy as np
-from tqdm import tqdm
-
-
-def load_data(data_dir: str, matrix: bool = False, idx_clf: bool = False):
-    """
-    data_dir : data_dir is the directory that you want to load the data from
-    matrix : if you want y as [0,1,0]
-    idx_clf : if you want y as 1 or 2 or 3
-    """
-    data = []
-    labels = {}
-    labels_r = {}
-    idx = 0
-    if matrix:
-        for label in os.listdir(data_dir):
-            idx += 1
-            labels[label] = idx
-            labels_r[idx] = label
-        for folder in tqdm(os.listdir(data_dir)):
-            for file in tqdm(os.listdir(f"{data_dir}{folder}/")):
-                img = cv2.imread(f"{data_dir}{folder}/{file}")
-                img = cv2.resize(img, (56, 56))
-                img = img / 255.0
-                data.append([img, np.eye(labels[folder] + 1, len(labels))[labels[folder] - 1]])
-        X = []
-        y = []
-        for d in tqdm(data):
-            X.append(d[0])
-            y.append(d[1])
-    if idx_clf:
-        for folder in os.listdir(data_dir):
-            idx += 1
-            for file in os.listdir(f"{data_dir}{folder}/"):
-                img = cv2.imread(f"{data_dir}{folder}/{file}")
-                img = cv2.resize(img, (56, 56))
-                img = img / 255.0
-                data.append([img, idx])
-        X = []
-        y = []
-        for d in data:
-            X.append(d[0])
-            y.append(d[1])
-    return X, y, labels, labels_r, idx, data

From fe9c5ccf2b020841f32d92498939006f668e1f92 Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Sat, 9 Oct 2021 11:58:45 +0530
Subject: [PATCH 41/53] Delete nlp.py

---
 pytorch_lightning/utilities/nlp.py | 61 ------------------------------
 1 file changed, 61 deletions(-)
 delete mode 100644 pytorch_lightning/utilities/nlp.py

diff --git a/pytorch_lightning/utilities/nlp.py b/pytorch_lightning/utilities/nlp.py
deleted file mode 100644
index 9ac33a429eb59..0000000000000
--- a/pytorch_lightning/utilities/nlp.py
+++ /dev/null
@@ -1,61 +0,0 @@
-import nltk
-import numpy as np
-import torch
-from nltk.stem.porter import PorterStemmer
-from sklearn.model_selection import train_test_split
-from tqdm import tqdm
-
-stemmer = PorterStemmer()
-
-
-def tokenize(sentence) -> list:
-    return nltk.word_tokenize(sentence)
-
-
-def stem(word) -> str:
-    return stemmer.stem(word.lower())
-
-
-def bag_of_words(tokenized_words, all_words):
-    tokenized_words = [stem(w) for w in tokenized_words]
-    bag = np.zeros(len(all_words))
-    for idx, w in enumerate(all_words):
-        if w in tokenized_words:
-            bag[idx] = 1.0
-    return bag
-
-
-def create_nlp_data(X, y, matrix_y: bool = False, test_size: float = 0.25):
-    data = []
-    labels = {}
-    labels_r = {}
-    idx = 0
-    words = []
-    for label in y:
-        if label not in list(labels.keys()):
-            idx += 1
-            labels[label] = 1
-    for X_batch, y_batch in tqdm(zip(X, y)):
-        X_batch = tokenize(X_batch)
-        new_X = []
-        for Xb in X_batch:
-            new_X.append(stem(Xb))
-        words.extend(new_X)
-        if matrix_y is True:
-            data.append([new_X, np.eye(labels[y_batch], len(labels))[labels[y_batch] - 1]])
-        else:
-            data.append([new_X, labels[y_batch]])
-    words = sorted(set(words))
-    np.random.shuffle(words)
-    np.random.shuffle(data)
-    X = []
-    y = []
-    for sentence, tag in tqdm(data):
-        X.append(bag_of_words(sentence, words))
-        y.append(tag)
-    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=test_size, shuffle=False)
-    X_train = torch.from_numpy(np.array(X_train)).float()
-    y_train = torch.from_numpy(np.array(y_train)).float()
-    X_test = torch.from_numpy(np.array(X_test)).float()
-    y_test = torch.from_numpy(np.array(y_test)).float()
-    return X_train, X_test, y_train, y_test, X, y, data, words, labels, labels_r

From 500b1f086a67e14259830de701a236261fa314bf Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Sat, 9 Oct 2021 11:59:02 +0530
Subject: [PATCH 42/53] Update requirements.txt

---
 requirements.txt | 5 +----
 1 file changed, 1 insertion(+), 4 deletions(-)

diff --git a/requirements.txt b/requirements.txt
index 339847b13010a..2b0f7c04f19f8 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,16 +1,13 @@
 # the default package dependencies
 
 numpy>=1.17.2
-torch>=1.8
+torch>=1.6
 future>=0.17.1  # required for builtins in setup.py
 tqdm>=4.41.0
 PyYAML>=5.1
 fsspec[http]>=2021.05.0, !=2021.06.0
 tensorboard>=2.2.0
 torchmetrics>=0.4.1
-scikit-learn>=0.18.1
-nltk>=3.6.3
 pyDeprecate==0.3.1
 packaging>=17.0
 typing-extensions  # TypedDict support for python<3.8
-opencv-python>=4.5.3.56

From dfaeb641086f513d8f217d78de6261e69f92f039 Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Sat, 9 Oct 2021 12:19:44 +0530
Subject: [PATCH 43/53] Update model_checkpoint.py

---
 pytorch_lightning/callbacks/model_checkpoint.py | 7 ++-----
 1 file changed, 2 insertions(+), 5 deletions(-)

diff --git a/pytorch_lightning/callbacks/model_checkpoint.py b/pytorch_lightning/callbacks/model_checkpoint.py
index 188cc9052aab5..78a05a8f5f608 100644
--- a/pytorch_lightning/callbacks/model_checkpoint.py
+++ b/pytorch_lightning/callbacks/model_checkpoint.py
@@ -147,7 +147,7 @@ class ModelCheckpoint(Callback):
 
     Raises:
         MisconfigurationException:
-            If ``save_top_k`` is neither ``None`` nor more than or equal to ``-1``,
+            If ``save_top_k`` is neither ``0`` nor more than or equal to ``-1``,
             if ``monitor`` is ``None`` and ``save_top_k`` is none of ``None``, ``-1``, and ``0``, or
             if ``mode`` is none of ``"min"`` or ``"max"``.
         ValueError:
@@ -222,9 +222,6 @@ def __init__(
         self.verbose = verbose
         self.save_last = save_last
         self.save_top_k = save_top_k
-        # TODO : The error is from #9868 do a better fix for the bug this is a solution for now
-        if self.save_top_k is None:
-            self.save_top_k = 0
         self.save_weights_only = save_weights_only
         self.auto_insert_metric_name = auto_insert_metric_name
         self._save_on_train_epoch_end = save_on_train_epoch_end
@@ -432,7 +429,7 @@ def __validate_init_configuration(self) -> None:
                 )
             if self.save_last:
                 rank_zero_warn(
-                    "ModelCheckpoint(save_last=True, save_top_k=None, monitor=None) is a redundant configuration."
+                    "ModelCheckpoint(save_last=True, save_top_k=0, monitor=None) is a redundant configuration."
                     " You can save the last checkpoint with ModelCheckpoint(save_top_k=None, monitor=None)."
                 )
             if self.save_top_k == -1 and self.save_last:

From 2162f62ace33cc35660a6966b05a7aefbbd7ccca Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Sun, 10 Oct 2021 14:54:47 +0530
Subject: [PATCH 44/53] Update README.md


From 83f379eb4f3309d1b4a11e42994306fc22997f7e Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Mon, 11 Oct 2021 07:28:13 +0530
Subject: [PATCH 45/53] Update pytorch_lightning/callbacks/model_checkpoint.py
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

Co-authored-by: Adrian Wälchli <aedu.waelchli@gmail.com>
---
 pytorch_lightning/callbacks/model_checkpoint.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/pytorch_lightning/callbacks/model_checkpoint.py b/pytorch_lightning/callbacks/model_checkpoint.py
index 78a05a8f5f608..1339d3ee98ca1 100644
--- a/pytorch_lightning/callbacks/model_checkpoint.py
+++ b/pytorch_lightning/callbacks/model_checkpoint.py
@@ -147,7 +147,7 @@ class ModelCheckpoint(Callback):
 
     Raises:
         MisconfigurationException:
-            If ``save_top_k`` is neither ``0`` nor more than or equal to ``-1``,
+            If ``save_top_k`` is smaller than ``-1``,
             if ``monitor`` is ``None`` and ``save_top_k`` is none of ``None``, ``-1``, and ``0``, or
             if ``mode`` is none of ``"min"`` or ``"max"``.
         ValueError:

From fecfbc86f6c498cadae55fa6afb5f7367b23a96f Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Mon, 11 Oct 2021 07:56:40 +0530
Subject: [PATCH 46/53] Update CHANGELOG.md

---
 CHANGELOG.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index 00bd7c84b0fb9..a9772978d681b 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -435,6 +435,7 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Fixed bug where the training step output needed to be `deepcopy`-ed ([#9349](https://github.com/PyTorchLightning/pytorch-lightning/pull/9349))
 
+- Fix save_top_k warning in ModelCheckpoint callback ([#9875](https://github.com/PyTorchLightning/pytorch-lightning/pull/9875))
 
 - Fixed freeing data iterators in loop `on_run_end` ([#9386](https://github.com/PyTorchLightning/pytorch-lightning/pull/9386))
 

From 3dc3337347b67a44e04e94aa556f8ac0b9cc896c Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Mon, 11 Oct 2021 15:59:23 +0530
Subject: [PATCH 47/53] Update test_model_checkpoint.py

---
 tests/checkpointing/test_model_checkpoint.py | 10 ----------
 1 file changed, 10 deletions(-)

diff --git a/tests/checkpointing/test_model_checkpoint.py b/tests/checkpointing/test_model_checkpoint.py
index ed2da81dbdeda..20a58cd948102 100644
--- a/tests/checkpointing/test_model_checkpoint.py
+++ b/tests/checkpointing/test_model_checkpoint.py
@@ -515,16 +515,6 @@ def test_none_monitor_top_k(tmpdir):
     ModelCheckpoint(dirpath=tmpdir, save_top_k=0)
     ModelCheckpoint(dirpath=tmpdir, save_top_k=1)
 
-
-def test_none_monitor_save_last(tmpdir):
-    """Test that a warning appears for save_last=True with monitor=None."""
-    with pytest.warns(UserWarning, match=r"ModelCheckpoint.*is a redundant.*"):
-        ModelCheckpoint(dirpath=tmpdir, save_last=True)
-    # These should not fail
-    ModelCheckpoint(dirpath=tmpdir, save_last=None)
-    ModelCheckpoint(dirpath=tmpdir, save_last=False)
-
-
 def test_invalid_every_n_epochs(tmpdir):
     """Make sure that a MisconfigurationException is raised for a negative every_n_epochs argument."""
     with pytest.raises(MisconfigurationException, match=r".*Must be >= 0"):

From a3e7581063c515fa11358a17ae0abac3dfd5089e Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Mon, 11 Oct 2021 10:30:47 +0000
Subject: [PATCH 48/53] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 tests/checkpointing/test_model_checkpoint.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/tests/checkpointing/test_model_checkpoint.py b/tests/checkpointing/test_model_checkpoint.py
index 20a58cd948102..5664458564993 100644
--- a/tests/checkpointing/test_model_checkpoint.py
+++ b/tests/checkpointing/test_model_checkpoint.py
@@ -515,6 +515,7 @@ def test_none_monitor_top_k(tmpdir):
     ModelCheckpoint(dirpath=tmpdir, save_top_k=0)
     ModelCheckpoint(dirpath=tmpdir, save_top_k=1)
 
+
 def test_invalid_every_n_epochs(tmpdir):
     """Make sure that a MisconfigurationException is raised for a negative every_n_epochs argument."""
     with pytest.raises(MisconfigurationException, match=r".*Must be >= 0"):

From acf6e2830b120c7c5e28f19df826735fc9dae357 Mon Sep 17 00:00:00 2001
From: Ranuga-Disansa <79456372+Programmer-RD-AI@users.noreply.github.com>
Date: Mon, 11 Oct 2021 16:05:40 +0530
Subject: [PATCH 49/53] Update model_checkpoint.py

---
 pytorch_lightning/callbacks/model_checkpoint.py | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/pytorch_lightning/callbacks/model_checkpoint.py b/pytorch_lightning/callbacks/model_checkpoint.py
index 1339d3ee98ca1..9ea6d0edd471c 100644
--- a/pytorch_lightning/callbacks/model_checkpoint.py
+++ b/pytorch_lightning/callbacks/model_checkpoint.py
@@ -432,11 +432,11 @@ def __validate_init_configuration(self) -> None:
                     "ModelCheckpoint(save_last=True, save_top_k=0, monitor=None) is a redundant configuration."
                     " You can save the last checkpoint with ModelCheckpoint(save_top_k=None, monitor=None)."
                 )
-            if self.save_top_k == -1 and self.save_last:
-                rank_zero_info(
-                    "ModelCheckpoint(save_last=True, save_top_k=-1, monitor=None)"
-                    " will duplicate the last checkpoint saved."
-                )
+#             if self.save_top_k == -1 and self.save_last:
+#                 rank_zero_info(
+#                     "ModelCheckpoint(save_last=True, save_top_k=-1, monitor=None)"
+#                     " will duplicate the last checkpoint saved."
+#                 )
 
     def __init_ckpt_dir(self, dirpath: Optional[_PATH], filename: Optional[str]) -> None:
         self._fs = get_filesystem(dirpath if dirpath else "")

From 73c0ae9ae21eef328dbaaeb6b042d1244a0bc708 Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Mon, 11 Oct 2021 10:36:46 +0000
Subject: [PATCH 50/53] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 pytorch_lightning/callbacks/model_checkpoint.py | 11 ++++++-----
 1 file changed, 6 insertions(+), 5 deletions(-)

diff --git a/pytorch_lightning/callbacks/model_checkpoint.py b/pytorch_lightning/callbacks/model_checkpoint.py
index 9ea6d0edd471c..3cb7e94ef9d68 100644
--- a/pytorch_lightning/callbacks/model_checkpoint.py
+++ b/pytorch_lightning/callbacks/model_checkpoint.py
@@ -432,11 +432,12 @@ def __validate_init_configuration(self) -> None:
                     "ModelCheckpoint(save_last=True, save_top_k=0, monitor=None) is a redundant configuration."
                     " You can save the last checkpoint with ModelCheckpoint(save_top_k=None, monitor=None)."
                 )
-#             if self.save_top_k == -1 and self.save_last:
-#                 rank_zero_info(
-#                     "ModelCheckpoint(save_last=True, save_top_k=-1, monitor=None)"
-#                     " will duplicate the last checkpoint saved."
-#                 )
+
+    #             if self.save_top_k == -1 and self.save_last:
+    #                 rank_zero_info(
+    #                     "ModelCheckpoint(save_last=True, save_top_k=-1, monitor=None)"
+    #                     " will duplicate the last checkpoint saved."
+    #                 )
 
     def __init_ckpt_dir(self, dirpath: Optional[_PATH], filename: Optional[str]) -> None:
         self._fs = get_filesystem(dirpath if dirpath else "")

From c56bcb87d1f527a1e47aa1045c5cf9a578fe36cf Mon Sep 17 00:00:00 2001
From: Rohit Gupta <rohitgr1998@gmail.com>
Date: Mon, 11 Oct 2021 17:27:54 +0530
Subject: [PATCH 51/53] update

---
 pytorch_lightning/callbacks/model_checkpoint.py | 15 +++++----------
 1 file changed, 5 insertions(+), 10 deletions(-)

diff --git a/pytorch_lightning/callbacks/model_checkpoint.py b/pytorch_lightning/callbacks/model_checkpoint.py
index 3cb7e94ef9d68..4101b82826da4 100644
--- a/pytorch_lightning/callbacks/model_checkpoint.py
+++ b/pytorch_lightning/callbacks/model_checkpoint.py
@@ -427,17 +427,12 @@ def __validate_init_configuration(self) -> None:
                     f"ModelCheckpoint(save_top_k={self.save_top_k}, monitor=None) is not a valid"
                     " configuration. No quantity for top_k to track."
                 )
-            if self.save_last:
-                rank_zero_warn(
-                    "ModelCheckpoint(save_last=True, save_top_k=0, monitor=None) is a redundant configuration."
-                    " You can save the last checkpoint with ModelCheckpoint(save_top_k=None, monitor=None)."
-                )
 
-    #             if self.save_top_k == -1 and self.save_last:
-    #                 rank_zero_info(
-    #                     "ModelCheckpoint(save_last=True, save_top_k=-1, monitor=None)"
-    #                     " will duplicate the last checkpoint saved."
-    #                 )
+            if self.save_top_k == -1 and self.save_last:
+                 rank_zero_info(
+                     "ModelCheckpoint(save_last=True, save_top_k=-1, monitor=None)"
+                     " will duplicate the last checkpoint saved."
+                 )
 
     def __init_ckpt_dir(self, dirpath: Optional[_PATH], filename: Optional[str]) -> None:
         self._fs = get_filesystem(dirpath if dirpath else "")

From ad6259dac0081dc3a8637734752c24359f40c6c3 Mon Sep 17 00:00:00 2001
From: Rohit Gupta <rohitgr1998@gmail.com>
Date: Mon, 11 Oct 2021 17:28:41 +0530
Subject: [PATCH 52/53] update

---
 pytorch_lightning/callbacks/model_checkpoint.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/pytorch_lightning/callbacks/model_checkpoint.py b/pytorch_lightning/callbacks/model_checkpoint.py
index 4101b82826da4..8d8dca9db5b24 100644
--- a/pytorch_lightning/callbacks/model_checkpoint.py
+++ b/pytorch_lightning/callbacks/model_checkpoint.py
@@ -429,10 +429,10 @@ def __validate_init_configuration(self) -> None:
                 )
 
             if self.save_top_k == -1 and self.save_last:
-                 rank_zero_info(
-                     "ModelCheckpoint(save_last=True, save_top_k=-1, monitor=None)"
-                     " will duplicate the last checkpoint saved."
-                 )
+                rank_zero_info(
+                    "ModelCheckpoint(save_last=True, save_top_k=-1, monitor=None)"
+                    " will duplicate the last checkpoint saved."
+                )
 
     def __init_ckpt_dir(self, dirpath: Optional[_PATH], filename: Optional[str]) -> None:
         self._fs = get_filesystem(dirpath if dirpath else "")

From 4a51af587817bf4effbf14d093099641249f5096 Mon Sep 17 00:00:00 2001
From: Rohit Gupta <rohitgr1998@gmail.com>
Date: Mon, 11 Oct 2021 17:30:46 +0530
Subject: [PATCH 53/53] chlog update

---
 CHANGELOG.md | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/CHANGELOG.md b/CHANGELOG.md
index a9772978d681b..bf426c3fa0371 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -418,6 +418,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 - Removed `TrainerProperties` mixin and moved property definitions directly into `Trainer` ([#9495](https://github.com/PyTorchLightning/pytorch-lightning/pull/9495))
 
 
+- Removed a redundant warning with `ModelCheckpoint(monitor=None)` callback ([#9875](https://github.com/PyTorchLightning/pytorch-lightning/pull/9875))
+
+
 ### Fixed
 
 
@@ -435,7 +438,6 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
 
 - Fixed bug where the training step output needed to be `deepcopy`-ed ([#9349](https://github.com/PyTorchLightning/pytorch-lightning/pull/9349))
 
-- Fix save_top_k warning in ModelCheckpoint callback ([#9875](https://github.com/PyTorchLightning/pytorch-lightning/pull/9875))
 
 - Fixed freeing data iterators in loop `on_run_end` ([#9386](https://github.com/PyTorchLightning/pytorch-lightning/pull/9386))