mirror of
https://github.com/saymrwulf/pytorch.git
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8286ce1e3a
Summary: Closes https://github.com/caffe2/caffe2/pull/1260 Differential Revision: D5906739 Pulled By: Yangqing fbshipit-source-id: e482ba9ba60b5337d9165f28f7ec68d4518a0902
89 lines
3.5 KiB
Python
89 lines
3.5 KiB
Python
# Copyright (c) 2016-present, Facebook, Inc.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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##############################################################################
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from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from __future__ import unicode_literals
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from hypothesis import assume, given
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import hypothesis.strategies as st
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import numpy as np
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from caffe2.proto import caffe2_pb2
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from caffe2.python import core
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import caffe2.python.hypothesis_test_util as hu
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class TestDropout(hu.HypothesisTestCase):
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@given(X=hu.tensor(),
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in_place=st.booleans(),
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ratio=st.floats(0, 0.999),
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engine=st.sampled_from(["", "CUDNN"]),
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**hu.gcs)
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def test_dropout_is_test(self, X, in_place, ratio, engine, gc, dc):
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"""Test with is_test=True for a deterministic reference impl."""
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# TODO(lukeyeager): enable this path when the GPU path is fixed
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if in_place:
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# Skip if trying in-place on GPU
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assume(not (gc.device_type == caffe2_pb2.CUDA and engine == ''))
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# If in-place on CPU, don't compare with GPU
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dc = dc[:1]
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op = core.CreateOperator("Dropout", ["X"],
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["X" if in_place else "Y"],
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ratio=ratio, engine=engine, is_test=True)
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self.assertDeviceChecks(dc, op, [X], [0])
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# No sense in checking gradients for test phase
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def reference_dropout_test(x):
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return x, np.ones(x.shape, dtype=np.bool)
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self.assertReferenceChecks(
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gc, op, [X], reference_dropout_test,
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# The 'mask' output may be uninitialized
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outputs_to_check=[0])
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@given(X=hu.tensor(),
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in_place=st.booleans(),
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output_mask=st.booleans(),
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engine=st.sampled_from(["", "CUDNN"]),
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**hu.gcs)
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def test_dropout_ratio0(self, X, in_place, output_mask, engine, gc, dc):
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"""Test with ratio=0 for a deterministic reference impl."""
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# TODO(lukeyeager): enable this path when the op is fixed
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if in_place:
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# Skip if trying in-place on GPU
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assume(gc.device_type != caffe2_pb2.CUDA)
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# If in-place on CPU, don't compare with GPU
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dc = dc[:1]
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is_test = not output_mask
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op = core.CreateOperator("Dropout", ["X"],
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["X" if in_place else "Y"] +
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(["mask"] if output_mask else []),
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ratio=0.0, engine=engine,
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is_test=is_test)
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self.assertDeviceChecks(dc, op, [X], [0])
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if not is_test:
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self.assertGradientChecks(gc, op, [X], 0, [0])
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def reference_dropout_ratio0(x):
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return (x,) if is_test else (x, np.ones(x.shape, dtype=np.bool))
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self.assertReferenceChecks(
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gc, op, [X], reference_dropout_ratio0,
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# Don't check the mask with cuDNN because it's packed data
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outputs_to_check=None if engine != 'CUDNN' else [0])
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