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rocal_pybind - bug fix for one hot encoded labels #1038

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merged 3 commits into from
Feb 15, 2023
Merged

rocal_pybind - bug fix for one hot encoded labels #1038

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a495e83
one hot label bug fix
LakshmiKumar23 Feb 8, 2023
5be3c65
adding comments
LakshmiKumar23 Feb 8, 2023
7d4498f
removing duplicate functions
LakshmiKumar23 Feb 9, 2023
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14 changes: 8 additions & 6 deletions rocAL/rocAL_pybind/amd/rocal/pipeline.py
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Original file line number Diff line number Diff line change
Expand Up @@ -217,13 +217,15 @@ def copyToTensorNCHW(self, array, multiplier, offset, reverse_channels, tensor_
multiplier[0], multiplier[1], multiplier[2], offset[0], offset[1], offset[2], (1 if reverse_channels else 0))
def GetOneHotEncodedLabels(self, array, device):
if device=="cpu":
return b.getOneHotEncodedLabels(self._handle, ctypes.c_void_p(array.data_ptr()), self._numOfClasses, 0)
if (isinstance(array,np.ndarray)):
b.getOneHotEncodedLabels(self._handle, array.ctypes.data_as(ctypes.c_void_p), self._numOfClasses, 0)
else: #torch tensor
return b.getOneHotEncodedLabels(self._handle, ctypes.c_void_p(array.data_ptr()), self._numOfClasses, 0)
if device=="gpu":
return b.getOneHotEncodedLabels(self._handle, ctypes.c_void_p(array.data_ptr()), self._numOfClasses, 1)

def GetOneHotEncodedLabels_TF(self, array):
# Host destination only
return b.getOneHotEncodedLabels(self._handle, array.ctypes.data_as(ctypes.c_void_p), self._numOfClasses, 0)
if (isinstance(array,cp.ndarray)):
b.getOneHotEncodedLabels(self._handle, array.data.ptr, self._numOfClasses, 1)
else: #torch tensor
return b.getOneHotEncodedLabels(self._handle, ctypes.c_void_p(array.data_ptr()), self._numOfClasses, 1)

def set_outputs(self, *output_list):
self._output_list_length = len(output_list)
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2 changes: 1 addition & 1 deletion rocAL/rocAL_pybind/amd/rocal/plugin/generic.py
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Expand Up @@ -133,7 +133,7 @@ def __next__(self):
if(self.loader._name == "labelReader"):
if(self.loader._oneHotEncoding == True):
self.loader.GetOneHotEncodedLabels(self.labels, self.device)
self.labels_tensor = self.labels.view(-1, self.bs, self.loader._numOfClasses).long()
self.labels_tensor = self.labels.reshape(-1, self.bs, self.loader._numOfClasses)
else:
if self.display:
for i in range(self.bs):
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2 changes: 1 addition & 1 deletion rocAL/rocAL_pybind/amd/rocal/plugin/tf.py
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Original file line number Diff line number Diff line change
Expand Up @@ -155,7 +155,7 @@ def __next__(self):
elif (self.loader._name == "TFRecordReaderClassification"):
if(self.loader._oneHotEncoding == True):
self.labels = np.zeros((self.bs)*(self.loader._numOfClasses),dtype = "int32")
self.loader.GetOneHotEncodedLabels_TF(self.labels)
self.loader.GetOneHotEncodedLabels(self.labels, device="cpu")
self.labels = np.reshape(self.labels, (-1, self.bs, self.loader._numOfClasses))
else:
self.labels = np.zeros((self.bs),dtype = "int32")
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