wehub-resource-sync
184 lines
5.1 KiB
Python
184 lines
5.1 KiB
Python
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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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# Note:
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# 0D Tensor indicates that the tensor's dimension is 0
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# 0D Tensor's shape is always [], numel is 1
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# which can be created by paddle.rand([])
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import unittest
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import paddle
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unary_api_list = [
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paddle.nn.functional.elu,
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paddle.nn.functional.rrelu,
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paddle.frac,
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paddle.sgn,
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paddle.nan_to_num,
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paddle.i0,
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paddle.i0e,
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paddle.i1,
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paddle.i1e,
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paddle.nn.functional.gelu,
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paddle.nn.functional.hardsigmoid,
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paddle.nn.functional.hardswish,
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paddle.nn.functional.hardshrink,
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paddle.nn.functional.hardtanh,
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paddle.nn.functional.leaky_relu,
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paddle.nn.functional.log_sigmoid,
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paddle.nn.functional.relu,
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paddle.nn.functional.relu6,
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paddle.nn.functional.sigmoid,
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paddle.nn.functional.softplus,
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paddle.nn.functional.softshrink,
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paddle.nn.functional.softsign,
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paddle.nn.functional.swish,
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paddle.nn.functional.tanhshrink,
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paddle.nn.functional.thresholded_relu,
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paddle.stanh,
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paddle.nn.functional.celu,
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paddle.nn.functional.selu,
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paddle.nn.functional.mish,
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paddle.nn.functional.silu,
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paddle.nn.functional.tanh,
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paddle.nn.functional.dropout,
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paddle.cosh,
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paddle.sinh,
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paddle.abs,
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paddle.acos,
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paddle.asin,
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paddle.atan,
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paddle.ceil,
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paddle.cos,
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paddle.exp,
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paddle.floor,
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paddle.log,
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paddle.log1p,
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paddle.reciprocal,
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paddle.round,
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paddle.sin,
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paddle.sqrt,
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paddle.square,
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paddle.tanh,
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paddle.acosh,
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paddle.asinh,
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paddle.atanh,
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paddle.expm1,
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paddle.log10,
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paddle.log2,
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paddle.tan,
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paddle.erf,
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paddle.erfinv,
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paddle.rsqrt,
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paddle.sign,
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paddle.deg2rad,
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paddle.rad2deg,
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paddle.neg,
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paddle.logit,
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paddle.trunc,
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paddle.digamma,
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paddle.lgamma,
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paddle.poisson,
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paddle.bernoulli,
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paddle.nn.functional.softmax,
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paddle.nn.functional.log_softmax,
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paddle.nn.functional.gumbel_softmax,
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paddle.nn.functional.alpha_dropout,
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]
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inplace_unary_api_list = [
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paddle.nn.functional.relu_,
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paddle.nn.functional.tanh_,
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paddle.tensor.sigmoid_,
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paddle.tensor.ceil_,
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paddle.tensor.floor_,
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paddle.tensor.reciprocal_,
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paddle.tensor.exp_,
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paddle.tensor.sqrt_,
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]
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# Use to test zero-dim in unary API.
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class TestUnaryAPI(unittest.TestCase):
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def test_dygraph_unary(self):
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paddle.disable_static()
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for api in unary_api_list:
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x = paddle.rand([])
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x.stop_gradient = False
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out = api(x)
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out.retain_grads()
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out.backward()
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self.assertEqual(x.shape, [])
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self.assertEqual(out.shape, [])
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if x.grad is not None:
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self.assertEqual(x.grad.shape, [])
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self.assertEqual(out.grad.shape, [])
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for api in inplace_unary_api_list:
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x = paddle.rand([])
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out = api(x)
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self.assertEqual(x.shape, [])
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self.assertEqual(out.shape, [])
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paddle.enable_static()
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def test_static_unary(self):
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paddle.enable_static()
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for api in unary_api_list:
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main_prog = paddle.static.Program()
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block = main_prog.global_block()
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exe = paddle.static.Executor()
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with paddle.static.program_guard(
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main_prog, paddle.static.Program()
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):
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x = paddle.rand([])
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x.stop_gradient = False
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out = api(x)
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fetch_list = [x, out]
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grad_list = paddle.static.append_backward(
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out, parameter_list=fetch_list
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)
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fetch_list.extend(
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[
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_grad
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for _param, _grad in grad_list
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if isinstance(
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_grad,
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(paddle.pir.Value, paddle.base.framework.Variable),
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)
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]
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)
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# 1) Test Program
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res = exe.run(main_prog, fetch_list=fetch_list)
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for item in res:
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self.assertEqual(item.shape, ())
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# 2) Test CompiledProgram Program
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if not paddle.framework.in_pir_mode():
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compile_prog = paddle.static.CompiledProgram(main_prog)
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res = exe.run(compile_prog, fetch_list=fetch_list)
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for item in res:
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self.assertEqual(item.shape, ())
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paddle.disable_static()
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if __name__ == "__main__":
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unittest.main()
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