mirror of
https://github.com/saymrwulf/pytorch.git
synced 2026-05-15 21:00:47 +00:00
8286ce1e3a
Summary: Closes https://github.com/caffe2/caffe2/pull/1260 Differential Revision: D5906739 Pulled By: Yangqing fbshipit-source-id: e482ba9ba60b5337d9165f28f7ec68d4518a0902
125 lines
4.3 KiB
Python
125 lines
4.3 KiB
Python
# Copyright (c) 2016-present, Facebook, Inc.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
##############################################################################
|
|
|
|
from __future__ import absolute_import
|
|
from __future__ import division
|
|
from __future__ import print_function
|
|
from __future__ import unicode_literals
|
|
|
|
import numpy as np
|
|
|
|
from hypothesis import given
|
|
import hypothesis.strategies as st
|
|
|
|
from caffe2.python import core
|
|
import caffe2.python.hypothesis_test_util as hu
|
|
|
|
|
|
class TestActivations(hu.HypothesisTestCase):
|
|
@given(X=hu.tensor(),
|
|
alpha=st.floats(min_value=0.1, max_value=2.0),
|
|
inplace=st.booleans(),
|
|
**hu.gcs)
|
|
def test_elu(self, X, alpha, inplace, gc, dc):
|
|
# go away from the origin point to avoid kink problems
|
|
X += 0.04 * np.sign(X)
|
|
X[X == 0.0] += 0.04
|
|
|
|
def elu_ref(X):
|
|
Y = X.copy()
|
|
neg_indices = X <= 0
|
|
Y[neg_indices] = alpha * (np.exp(Y[neg_indices]) - 1)
|
|
return (Y,)
|
|
|
|
op = core.CreateOperator(
|
|
"Elu",
|
|
["X"], ["Y" if not inplace else "X"],
|
|
alpha=alpha)
|
|
self.assertReferenceChecks(gc, op, [X], elu_ref)
|
|
# Check over multiple devices
|
|
self.assertDeviceChecks(dc, op, [X], [0])
|
|
# Gradient check wrt X
|
|
self.assertGradientChecks(gc, op, [X], 0, [0])
|
|
|
|
@given(X=hu.tensor(min_dim=4, max_dim=4),
|
|
alpha=st.floats(min_value=0.1, max_value=2.0),
|
|
inplace=st.booleans(),
|
|
shared=st.booleans(),
|
|
order=st.sampled_from(["NCHW", "NHWC"]),
|
|
seed=st.sampled_from([20, 100]),
|
|
**hu.gcs)
|
|
def test_prelu(self, X, alpha, inplace, shared, order, seed, gc, dc):
|
|
np.random.seed(seed)
|
|
W = np.random.randn(
|
|
X.shape[1] if order == "NCHW" else X.shape[3]).astype(np.float32)
|
|
|
|
if shared:
|
|
W = np.random.randn(1).astype(np.float32)
|
|
|
|
# go away from the origin point to avoid kink problems
|
|
X += 0.04 * np.sign(X)
|
|
X[X == 0.0] += 0.04
|
|
|
|
def prelu_ref(X, W):
|
|
Y = X.copy()
|
|
W = W.reshape(1, -1, 1, 1) if order == "NCHW" \
|
|
else W.reshape(1, 1, 1, -1)
|
|
assert len(X.shape) == 4
|
|
neg_indices = X <= 0
|
|
assert len(neg_indices.shape) == 4
|
|
assert X.shape == neg_indices.shape
|
|
Y[neg_indices] = (Y * W)[neg_indices]
|
|
return (Y,)
|
|
|
|
op = core.CreateOperator(
|
|
"PRelu", ["X", "W"], ["Y" if not inplace else "X"],
|
|
alpha=alpha, order=order)
|
|
self.assertReferenceChecks(gc, op, [X, W], prelu_ref)
|
|
# Check over multiple devices
|
|
self.assertDeviceChecks(dc, op, [X, W], [0])
|
|
|
|
if not inplace:
|
|
# Gradient check wrt X
|
|
self.assertGradientChecks(gc, op, [X, W], 0, [0], stepsize=1e-2)
|
|
# Gradient check wrt W
|
|
self.assertGradientChecks(gc, op, [X, W], 1, [0], stepsize=1e-2)
|
|
|
|
@given(X=hu.tensor(),
|
|
alpha=st.floats(min_value=0.1, max_value=2.0),
|
|
inplace=st.booleans(),
|
|
**hu.gcs)
|
|
def test_leaky_relu(self, X, alpha, inplace, gc, dc):
|
|
# go away from the origin point to avoid kink problems
|
|
X += 0.04 * np.sign(X)
|
|
X[X == 0.0] += 0.04
|
|
|
|
def leaky_relu_ref(X):
|
|
Y = X.copy()
|
|
neg_indices = X <= 0
|
|
Y[neg_indices] = Y[neg_indices] * alpha
|
|
return (Y,)
|
|
|
|
op = core.CreateOperator(
|
|
"LeakyRelu",
|
|
["X"], ["Y" if not inplace else "X"],
|
|
alpha=alpha)
|
|
self.assertReferenceChecks(gc, op, [X], leaky_relu_ref)
|
|
# Check over multiple devices
|
|
self.assertDeviceChecks(dc, op, [X], [0])
|
|
|
|
|
|
if __name__ == "__main__":
|
|
import unittest
|
|
unittest.main()
|