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Typing fixes #17000

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Mar 8, 2023
Merged

Typing fixes #17000

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3 changes: 3 additions & 0 deletions src/lightning/pytorch/CHANGELOG.md
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Expand Up @@ -153,6 +153,9 @@ The format is based on [Keep a Changelog](http://keepachangelog.com/en/1.0.0/).
- Changed minimum supported version of `rich` from `10.14.0` to `12.13.0` ([#16798](https://github.com/Lightning-AI/lightning/pull/16798))


- The `ServableModule` is now an abstract interface ([#17000](https://github.com/Lightning-AI/lightning/pull/17000))


### Deprecated

-
Expand Down
7 changes: 6 additions & 1 deletion src/lightning/pytorch/serve/servable_module.py
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@@ -1,10 +1,11 @@
from abc import ABC, abstractmethod
from typing import Any, Callable, Dict, Tuple

import torch
from torch import Tensor


class ServableModule(torch.nn.Module):
class ServableModule(ABC, torch.nn.Module):

"""The ServableModule provides a simple API to make your model servable.

Expand Down Expand Up @@ -56,9 +57,11 @@ def configure_response(self):
assert serve_cb.resp.json() == {"output": [0, 1]}
"""

@abstractmethod
def configure_payload(self) -> Dict[str, Any]:
"""Returns a request payload as a dictionary."""

@abstractmethod
def configure_serialization(self) -> Tuple[Dict[str, Callable], Dict[str, Callable]]:
"""Returns a tuple of dictionaries.

Expand All @@ -69,6 +72,7 @@ def configure_serialization(self) -> Tuple[Dict[str, Callable], Dict[str, Callab
and the associated serialization function (e.g function to convert a tensors into payload).
"""

@abstractmethod
def serve_step(self, *args: Tensor, **kwargs: Tensor) -> Dict[str, Tensor]:
r"""
Returns the predictions of your model as a dictionary.
Expand All @@ -86,5 +90,6 @@ def serve_step(self, x: torch.Tensor) -> Dict[str, torch.Tensor]:
- ``dict`` - A dictionary with their associated tensors.
"""

@abstractmethod
def configure_response(self) -> Dict[str, Any]:
"""Returns a response to validate the server response."""
6 changes: 2 additions & 4 deletions src/lightning/pytorch/utilities/parsing.py
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Expand Up @@ -45,14 +45,12 @@ def clean_namespace(hparams: MutableMapping) -> None:
del hparams[k]


def parse_class_init_keys(
cls: Union[Type["pl.LightningModule"], Type["pl.LightningDataModule"]]
) -> Tuple[str, Optional[str], Optional[str]]:
def parse_class_init_keys(cls: Type) -> Tuple[str, Optional[str], Optional[str]]:
"""Parse key words for standard ``self``, ``*args`` and ``**kwargs``.

Examples:

>>> class Model():
>>> class Model:
... def __init__(self, hparams, *my_args, anykw=42, **my_kwargs):
... pass
>>> parse_class_init_keys(Model)
Expand Down
300 changes: 145 additions & 155 deletions src/lightning/pytorch/utilities/testing/_runif.py
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Expand Up @@ -17,7 +17,7 @@
from typing import Any, Optional

import torch
from lightning_utilities.core.imports import compare_version, module_available, RequirementCache
from lightning_utilities.core.imports import compare_version, RequirementCache
from packaging.version import Version

from lightning.fabric.accelerators.cuda import num_cuda_devices
Expand All @@ -31,15 +31,28 @@
from lightning.pytorch.strategies.deepspeed import _DEEPSPEED_AVAILABLE
from lightning.pytorch.utilities.imports import _OMEGACONF_AVAILABLE, _PSUTIL_AVAILABLE

if module_available("_pytest"):
from _pytest.mark import MarkDecorator
else:
MarkDecorator = Any

_SKLEARN_AVAILABLE = RequirementCache("scikit-learn")


class _RunIf:
def _RunIf(
min_cuda_gpus: int = 0,
min_torch: Optional[str] = None,
max_torch: Optional[str] = None,
min_python: Optional[str] = None,
bf16_cuda: bool = False,
tpu: bool = False,
ipu: bool = False,
hpu: bool = False,
mps: Optional[bool] = None,
skip_windows: bool = False,
standalone: bool = False,
deepspeed: bool = False,
rich: bool = False,
omegaconf: bool = False,
psutil: bool = False,
sklearn: bool = False,
onnx: bool = False,
) -> Any: # not the real return because it would require that pytest is available
"""Wrapper around ``pytest.mark.skipif`` with specific conditions.

Example:
Expand All @@ -48,152 +61,129 @@ class _RunIf:
@pytest.mark.parametrize("arg1", [1, 2.0])
def test_wrapper(arg1):
assert arg1 > 0.0
"""

def __new__(
self,
min_cuda_gpus: int = 0,
min_torch: Optional[str] = None,
max_torch: Optional[str] = None,
min_python: Optional[str] = None,
bf16_cuda: bool = False,
tpu: bool = False,
ipu: bool = False,
hpu: bool = False,
mps: Optional[bool] = None,
skip_windows: bool = False,
standalone: bool = False,
deepspeed: bool = False,
rich: bool = False,
omegaconf: bool = False,
psutil: bool = False,
sklearn: bool = False,
onnx: bool = False,
) -> MarkDecorator: # not the real return because it would require that pytest is available
"""Configure.

Args:
min_cuda_gpus: Require this number of gpus and that the ``PL_RUN_CUDA_TESTS=1`` environment variable is set.
min_torch: Require that PyTorch is greater or equal than this version.
max_torch: Require that PyTorch is less than this version.
min_python: Require that Python is greater or equal than this version.
bf16_cuda: Require that CUDA device supports bf16.
tpu: Require that TPU is available.
ipu: Require that IPU is available and that the ``PL_RUN_IPU_TESTS=1`` environment variable is set.
hpu: Require that HPU is available.
mps: If True: Require that MPS (Apple Silicon) is available,
if False: Explicitly Require that MPS is not available
skip_windows: Skip for Windows platform.
standalone: Mark the test as standalone, our CI will run it in a separate process.
This requires that the ``PL_RUN_STANDALONE_TESTS=1`` environment variable is set.
deepspeed: Require that microsoft/DeepSpeed is installed.
rich: Require that willmcgugan/rich is installed.
omegaconf: Require that omry/omegaconf is installed.
psutil: Require that psutil is installed.
sklearn: Require that scikit-learn is installed.
onnx: Require that onnx is installed.
"""
import pytest

conditions = []
reasons = []
kwargs: dict = {} # It's required for our CI to run under the different PL_RUN_X_TESTS

if min_cuda_gpus:
conditions.append(num_cuda_devices() < min_cuda_gpus)
reasons.append(f"GPUs>={min_cuda_gpus}")
# used in conftest.py::pytest_collection_modifyitems
kwargs["min_cuda_gpus"] = True

if min_torch:
# set use_base_version for nightly support
conditions.append(compare_version("torch", operator.lt, min_torch, use_base_version=True))
reasons.append(f"torch>={min_torch}, {torch.__version__} installed")

if max_torch:
# set use_base_version for nightly support
conditions.append(compare_version("torch", operator.ge, max_torch, use_base_version=True))
reasons.append(f"torch<{max_torch}, {torch.__version__} installed")

if min_python:
py_version = f"{sys.version_info.major}.{sys.version_info.minor}.{sys.version_info.micro}"
conditions.append(Version(py_version) < Version(min_python))
reasons.append(f"python>={min_python}")

if bf16_cuda:
try:
cond = not (torch.cuda.is_available() and torch.cuda.is_bf16_supported())
except (AssertionError, RuntimeError) as e:
# AssertionError: Torch not compiled with CUDA enabled
# RuntimeError: Found no NVIDIA driver on your system.
is_unrelated = "Found no NVIDIA driver" not in str(e) or "Torch not compiled with CUDA" not in str(e)
if is_unrelated:
raise e
cond = True

conditions.append(cond)
reasons.append("CUDA device bf16")

if skip_windows:
conditions.append(sys.platform == "win32")
reasons.append("unimplemented on Windows")

if tpu:
conditions.append(not TPUAccelerator.is_available())
reasons.append("TPU")
# used in conftest.py::pytest_collection_modifyitems
kwargs["tpu"] = True

if ipu:
conditions.append(not _IPU_AVAILABLE)
reasons.append("IPU")
# used in conftest.py::pytest_collection_modifyitems
kwargs["ipu"] = True

if hpu:
conditions.append(not _HPU_AVAILABLE)
reasons.append("HPU")

if mps is not None:
if mps:
conditions.append(not MPSAccelerator.is_available())
reasons.append("MPS")
else:
conditions.append(MPSAccelerator.is_available())
reasons.append("not MPS")

if standalone:
env_flag = os.getenv("PL_RUN_STANDALONE_TESTS", "0")
conditions.append(env_flag != "1")
reasons.append("Standalone execution")
# used in conftest.py::pytest_collection_modifyitems
kwargs["standalone"] = True

if deepspeed:
conditions.append(not _DEEPSPEED_AVAILABLE)
reasons.append("Deepspeed")

if rich:
conditions.append(not _RICH_AVAILABLE)
reasons.append("Rich")

if omegaconf:
conditions.append(not _OMEGACONF_AVAILABLE)
reasons.append("omegaconf")

if psutil:
conditions.append(not _PSUTIL_AVAILABLE)
reasons.append("psutil")

if sklearn:
conditions.append(not _SKLEARN_AVAILABLE)
reasons.append("scikit-learn")

if onnx:
conditions.append(_TORCH_GREATER_EQUAL_2_0 and not _ONNX_AVAILABLE)
reasons.append("onnx")

reasons = [rs for cond, rs in zip(conditions, reasons) if cond]
kwargs.pop("condition", None)
kwargs.pop("reason", None)
return pytest.mark.skipif(condition=any(conditions), reason=f"Requires: [{' + '.join(reasons)}]", **kwargs)
Args:
min_cuda_gpus: Require this number of gpus and that the ``PL_RUN_CUDA_TESTS=1`` environment variable is set.
min_torch: Require that PyTorch is greater or equal than this version.
max_torch: Require that PyTorch is less than this version.
min_python: Require that Python is greater or equal than this version.
bf16_cuda: Require that CUDA device supports bf16.
tpu: Require that TPU is available.
ipu: Require that IPU is available and that the ``PL_RUN_IPU_TESTS=1`` environment variable is set.
hpu: Require that HPU is available.
mps: If True: Require that MPS (Apple Silicon) is available,
if False: Explicitly Require that MPS is not available
skip_windows: Skip for Windows platform.
standalone: Mark the test as standalone, our CI will run it in a separate process.
This requires that the ``PL_RUN_STANDALONE_TESTS=1`` environment variable is set.
deepspeed: Require that microsoft/DeepSpeed is installed.
rich: Require that willmcgugan/rich is installed.
omegaconf: Require that omry/omegaconf is installed.
psutil: Require that psutil is installed.
sklearn: Require that scikit-learn is installed.
onnx: Require that onnx is installed.
"""
import pytest

conditions = []
reasons = []
kwargs: dict = {} # It's required for our CI to run under the different PL_RUN_X_TESTS

if min_cuda_gpus:
conditions.append(num_cuda_devices() < min_cuda_gpus)
reasons.append(f"GPUs>={min_cuda_gpus}")
# used in conftest.py::pytest_collection_modifyitems
kwargs["min_cuda_gpus"] = True

if min_torch:
# set use_base_version for nightly support
conditions.append(compare_version("torch", operator.lt, min_torch, use_base_version=True))
reasons.append(f"torch>={min_torch}, {torch.__version__} installed")

if max_torch:
# set use_base_version for nightly support
conditions.append(compare_version("torch", operator.ge, max_torch, use_base_version=True))
reasons.append(f"torch<{max_torch}, {torch.__version__} installed")

if min_python:
py_version = f"{sys.version_info.major}.{sys.version_info.minor}.{sys.version_info.micro}"
conditions.append(Version(py_version) < Version(min_python))
reasons.append(f"python>={min_python}")

if bf16_cuda:
try:
cond = not (torch.cuda.is_available() and torch.cuda.is_bf16_supported())
except (AssertionError, RuntimeError) as e:
# AssertionError: Torch not compiled with CUDA enabled
# RuntimeError: Found no NVIDIA driver on your system.
is_unrelated = "Found no NVIDIA driver" not in str(e) or "Torch not compiled with CUDA" not in str(e)
if is_unrelated:
raise e
cond = True

conditions.append(cond)
reasons.append("CUDA device bf16")

if skip_windows:
conditions.append(sys.platform == "win32")
reasons.append("unimplemented on Windows")

if tpu:
conditions.append(not TPUAccelerator.is_available())
reasons.append("TPU")
# used in conftest.py::pytest_collection_modifyitems
kwargs["tpu"] = True

if ipu:
conditions.append(not _IPU_AVAILABLE)
reasons.append("IPU")
# used in conftest.py::pytest_collection_modifyitems
kwargs["ipu"] = True

if hpu:
conditions.append(not _HPU_AVAILABLE)
reasons.append("HPU")

if mps is not None:
if mps:
conditions.append(not MPSAccelerator.is_available())
reasons.append("MPS")
else:
conditions.append(MPSAccelerator.is_available())
reasons.append("not MPS")

if standalone:
env_flag = os.getenv("PL_RUN_STANDALONE_TESTS", "0")
conditions.append(env_flag != "1")
reasons.append("Standalone execution")
# used in conftest.py::pytest_collection_modifyitems
kwargs["standalone"] = True

if deepspeed:
conditions.append(not _DEEPSPEED_AVAILABLE)
reasons.append("Deepspeed")

if rich:
conditions.append(not _RICH_AVAILABLE)
reasons.append("Rich")

if omegaconf:
conditions.append(not _OMEGACONF_AVAILABLE)
reasons.append("omegaconf")

if psutil:
conditions.append(not _PSUTIL_AVAILABLE)
reasons.append("psutil")

if sklearn:
conditions.append(not _SKLEARN_AVAILABLE)
reasons.append("scikit-learn")

if onnx:
conditions.append(_TORCH_GREATER_EQUAL_2_0 and not _ONNX_AVAILABLE)
reasons.append("onnx")

reasons = [rs for cond, rs in zip(conditions, reasons) if cond]
kwargs.pop("condition", None)
kwargs.pop("reason", None)
return pytest.mark.skipif(condition=any(conditions), reason=f"Requires: [{' + '.join(reasons)}]", **kwargs)