52 lines
2.0 KiB
Python
52 lines
2.0 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 caffe2.python import core
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import caffe2.python.hypothesis_test_util as hu
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import functools
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from hypothesis import given
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import hypothesis.strategies as st
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import numpy as np
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class TestWeightScale(hu.HypothesisTestCase):
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@given(inputs=hu.tensors(n=1),
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ITER=st.integers(min_value=0, max_value=100),
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stepsize=st.integers(min_value=20, max_value=50),
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upper_bound_iter=st.integers(min_value=5, max_value=100),
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scale=st.floats(min_value=0.01, max_value=0.99, allow_nan=False, allow_infinity=False),
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**hu.gcs)
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def test_weight_scale(self, inputs, ITER, stepsize, upper_bound_iter, scale, gc, dc):
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ITER = np.array([ITER], dtype=np.int64)
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op = core.CreateOperator(
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"WeightScale", ["w", "iter"], ["nw"], stepsize=stepsize, upper_bound_iter=upper_bound_iter, scale=scale)
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def ref_weight_scale(w, iter, stepsize, upper_bound_iter, scale):
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iter = iter + 1
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return [w * scale if iter % stepsize == 0 and iter < upper_bound_iter else w]
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input_device_options = {'iter': hu.cpu_do}
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self.assertReferenceChecks(
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gc,
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op,
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[inputs[0], ITER],
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functools.partial(ref_weight_scale, stepsize=stepsize, upper_bound_iter=upper_bound_iter, scale=scale),
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input_device_options=input_device_options
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)
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