wehub-resource-sync
318 lines
10 KiB
Python
318 lines
10 KiB
Python
# Copyright (c) 2019 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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import os
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import sys
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import unittest
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sys.path.append("../../legacy_test")
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import numpy as np
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from op_test import OpTest, get_device_place, is_custom_device
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from test_attribute_var import UnittestBase
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import paddle
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from paddle import base
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from paddle.base import core, framework
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from paddle.framework import in_pir_mode
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class TestEyeOp(OpTest):
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def setUp(self):
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'''
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Test eye op with default shape
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'''
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self.python_api = paddle.eye
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self.op_type = "eye"
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self.prim_op_type = "comp"
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self.public_python_api = paddle.eye
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self.init_dtype()
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self.init_attrs()
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self.inputs = {}
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self.attrs = {
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'num_rows': self.num_columns,
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'num_columns': self.num_columns,
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'dtype': framework.convert_nptype_to_vartype(self.dtype),
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}
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self.outputs = {
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'Out': np.eye(self.num_rows, self.num_columns, dtype=self.dtype)
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}
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def test_check_output(self):
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if self.dtype == np.complex64 or self.dtype == np.complex128:
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self.check_output(check_pir=True)
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else:
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self.check_output(check_pir=True, check_prim_pir=True)
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def init_dtype(self):
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self.dtype = np.int32
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def init_attrs(self):
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self.num_rows = 319
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self.num_columns = 319
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class TestEyeOp1(OpTest):
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def setUp(self):
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'''
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Test eye op with default parameters
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'''
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self.python_api = paddle.eye
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self.op_type = "eye"
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self.prim_op_type = "comp"
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self.public_python_api = paddle.eye
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self.inputs = {}
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self.attrs = {'num_rows': 50}
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self.outputs = {'Out': np.eye(50, dtype=float)}
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def test_check_output(self):
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self.check_output(check_pir=True, check_prim_pir=True)
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class TestEyeOp2(OpTest):
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def setUp(self):
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'''
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Test eye op with specified shape
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'''
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self.python_api = paddle.eye
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self.op_type = "eye"
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self.prim_op_type = "comp"
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self.public_python_api = paddle.eye
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self.inputs = {}
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self.attrs = {'num_rows': 99, 'num_columns': 1}
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self.outputs = {'Out': np.eye(99, 1, dtype=float)}
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def test_check_output(self):
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self.check_output(check_pir=True, check_prim_pir=True)
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class TestEyeOp3(OpTest):
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def setUp(self):
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'''
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Test eye op with np.int32 scalar
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'''
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self.python_api = paddle.eye
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self.op_type = "eye"
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self.prim_op_type = "comp"
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self.public_python_api = paddle.eye
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self.inputs = {}
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self.attrs = {'num_rows': np.int32(99), 'num_columns': np.int32(1)}
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self.outputs = {'Out': np.eye(99, 1, dtype=float)}
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def test_check_output(self):
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self.check_output(check_pir=True, check_prim_pir=True)
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class API_TestTensorEye(unittest.TestCase):
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def test_static_out(self):
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with paddle.static.program_guard(paddle.static.Program()):
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data = paddle.eye(10)
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place = base.CPUPlace()
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exe = paddle.static.Executor(place)
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(result,) = exe.run(fetch_list=[data])
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expected_result = np.eye(10, dtype="float32")
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self.assertEqual((result == expected_result).all(), True)
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with paddle.static.program_guard(paddle.static.Program()):
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data = paddle.eye(10, num_columns=7, dtype="float64")
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place = paddle.CPUPlace()
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exe = paddle.static.Executor(place)
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(result,) = exe.run(fetch_list=[data])
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expected_result = np.eye(10, 7, dtype="float64")
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self.assertEqual((result == expected_result).all(), True)
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with paddle.static.program_guard(paddle.static.Program()):
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data = paddle.eye(10, dtype="int64")
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place = paddle.CPUPlace()
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exe = paddle.static.Executor(place)
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(result,) = exe.run(fetch_list=[data])
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expected_result = np.eye(10, dtype="int64")
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self.assertEqual((result == expected_result).all(), True)
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def test_dynamic_out(self):
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paddle.disable_static()
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out = paddle.eye(10, dtype="int64")
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expected_result = np.eye(10, dtype="int64")
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paddle.enable_static()
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self.assertEqual((out.numpy() == expected_result).all(), True)
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def test_errors(self):
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with paddle.static.program_guard(paddle.static.Program()):
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def test_num_rows_type_check():
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paddle.eye(-1, dtype="int64")
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self.assertRaises(TypeError, test_num_rows_type_check)
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def test_num_columns_type_check():
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paddle.eye(10, num_columns=5.2, dtype="int64")
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self.assertRaises(TypeError, test_num_columns_type_check)
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def test_num_columns_type_check1():
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paddle.eye(10, num_columns=10, dtype="int8")
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self.assertRaises(TypeError, test_num_columns_type_check1)
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class TestEyeRowsCol(UnittestBase):
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def init_info(self):
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self.shapes = [[2, 3, 4]]
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self.save_path = os.path.join(self.temp_dir.name, self.path_prefix())
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def test_static(self):
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main_prog = paddle.static.Program()
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startup_prog = paddle.static.Program()
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with paddle.static.program_guard(main_prog, startup_prog):
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fc = paddle.nn.Linear(4, 10)
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x = paddle.randn([2, 3, 4])
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x.stop_gradient = False
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feat = fc(x) # [2,3,10]
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tmp = self.call_func(feat)
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out = feat + tmp
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sgd = paddle.optimizer.SGD()
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sgd.minimize(paddle.mean(out))
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if not in_pir_mode():
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self.assertTrue(self.var_prefix() in str(main_prog))
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exe = paddle.static.Executor()
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exe.run(startup_prog)
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res = exe.run(fetch_list=[tmp, out])
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gt = np.eye(3, 10)
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np.testing.assert_allclose(res[0], gt)
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paddle.static.save_inference_model(
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self.save_path, [x], [tmp, out], exe
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)
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# Test for Inference Predictor
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infer_outs = self.infer_prog()
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np.testing.assert_allclose(infer_outs[0], gt)
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def path_prefix(self):
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return 'eye_rows_cols'
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def var_prefix(self):
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return "Var["
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def call_func(self, x):
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rows = paddle.assign(3)
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cols = paddle.assign(10)
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out = paddle.eye(rows, cols)
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return out
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def test_error(self):
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with self.assertRaises(TypeError):
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paddle.eye(-1)
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class TestEyeFP16OP(TestEyeOp):
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'''Test eye op with specified dtype'''
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def init_dtype(self):
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self.dtype = np.float16
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class TestEyeComplex64OP(TestEyeOp):
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'''Test eye op with specified dtype'''
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def init_dtype(self):
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self.dtype = np.complex64
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class TestEyeComplex128OP(TestEyeOp):
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'''Test eye op with specified dtype'''
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def init_dtype(self):
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self.dtype = np.complex128
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@unittest.skipIf(
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not (core.is_compiled_with_cuda() or is_custom_device())
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or not core.is_bfloat16_supported(get_device_place()),
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"core is not compiled with CUDA and not support the bfloat16",
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)
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class TestEyeBF16OP(OpTest):
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def setUp(self):
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self.op_type = "eye"
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self.dtype = np.uint16
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self.python_api = paddle.eye
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self.prim_op_type = "comp"
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self.public_python_api = paddle.eye
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self.inputs = {}
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self.attrs = {
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'num_rows': 219,
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'num_columns': 319,
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}
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self.outputs = {'Out': np.eye(219, 319)}
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def test_check_output(self):
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place = get_device_place()
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self.check_output_with_place(place, check_pir=True, check_prim_pir=True)
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class API_TestTensorEye_Compatibility(unittest.TestCase):
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def test_static_out(self):
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with paddle.static.program_guard(paddle.static.Program()):
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data = paddle.eye(n=10)
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place = base.CPUPlace()
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exe = paddle.static.Executor(place)
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(result,) = exe.run(fetch_list=[data])
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expected_result = np.eye(10, dtype="float32")
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self.assertEqual((result == expected_result).all(), True)
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with paddle.static.program_guard(paddle.static.Program()):
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data = paddle.eye(n=10, m=7, dtype="float64")
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place = paddle.CPUPlace()
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exe = paddle.static.Executor(place)
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(result,) = exe.run(fetch_list=[data])
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expected_result = np.eye(10, 7, dtype="float64")
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self.assertEqual((result == expected_result).all(), True)
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with paddle.static.program_guard(paddle.static.Program()):
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data = paddle.eye(n=10, dtype="int64")
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place = paddle.CPUPlace()
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exe = paddle.static.Executor(place)
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(result,) = exe.run(fetch_list=[data])
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expected_result = np.eye(10, dtype="int64")
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self.assertEqual((result == expected_result).all(), True)
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def test_dynamic_out(self):
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paddle.disable_static()
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out1 = paddle.eye(n=10, dtype="int64")
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expected_result1 = np.eye(10, dtype="int64")
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self.assertEqual((out1.numpy() == expected_result1).all(), True)
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out2 = paddle.eye(n=10, m=7, dtype="int64")
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expected_result2 = np.eye(10, 7, dtype="int64")
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self.assertEqual((out2.numpy() == expected_result2).all(), True)
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out3_2 = paddle.empty(shape=[10, 5], dtype="int64")
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out3_1 = paddle.eye(n=10, m=5, dtype="int64", out=out3_2)
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expected_result3 = np.eye(10, 5, dtype="int64")
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self.assertEqual((out3_1.numpy() == expected_result3).all(), True)
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self.assertEqual((out3_2.numpy() == expected_result3).all(), True)
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paddle.enable_static()
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if __name__ == "__main__":
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paddle.enable_static()
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unittest.main()
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