From bdc2c2dba855babb37e9d07a3b3da2050a88b89f Mon Sep 17 00:00:00 2001 From: wangchaochaohu Date: Sun, 12 Jul 2020 00:39:10 +0800 Subject: [PATCH] full Op:remove device, out and stop_gradient parameter for API 2.0 test=develop (#25257) --- python/paddle/fluid/layers/tensor.py | 33 +++--- .../tests/unittests/test_fill_constant_op.py | 109 ++---------------- .../fluid/tests/unittests/test_full_op.py | 43 +------ .../fluid/tests/unittests/test_ones_op.py | 83 +++++++++++++ .../fluid/tests/unittests/test_zeros_op.py | 43 +++++++ python/paddle/tensor/creation.py | 75 +++--------- 6 files changed, 174 insertions(+), 212 deletions(-) create mode 100644 python/paddle/fluid/tests/unittests/test_ones_op.py diff --git a/python/paddle/fluid/layers/tensor.py b/python/paddle/fluid/layers/tensor.py index e6a2d1ca86f..1b114695d67 100644 --- a/python/paddle/fluid/layers/tensor.py +++ b/python/paddle/fluid/layers/tensor.py @@ -620,7 +620,7 @@ def assign(input, output=None): return output -def fill_constant(shape, dtype, value, force_cpu=False, out=None): +def fill_constant(shape, dtype, value, force_cpu=False, out=None, name=None): """ :alias_main: paddle.fill_constant :alias: paddle.fill_constant,paddle.tensor.fill_constant,paddle.tensor.creation.fill_constant @@ -638,12 +638,14 @@ def fill_constant(shape, dtype, value, force_cpu=False, out=None): If ``shape`` is an Variable, it should be an 1-D Tensor . dtype(np.dtype|core.VarDesc.VarType|str): Data type of the output tensor which can be float16, float32, float64, int32, int64. - value(float16|float32|float64|int32|int64|Variable): The constant value used to initialize + value(bool|float|int|Variable): The constant value used to initialize the Tensor to be created. If value is an Variable, it should be an 1-D Tensor. force_cpu(bool): data should be on CPU if it's true, default value is False. out(Variable, optional): Optional output which can be any created Variable that meets the requirements to store the result of operation. if out is None, a new Varibale will be create to store the result. + name(str, optional): The default value is None. Normally there is no need for user to set this + property. For more information, please refer to :ref:`api_guide_Name`. Returns: Variable: Tensor which is created according to shape and dtype. @@ -666,19 +668,16 @@ def fill_constant(shape, dtype, value, force_cpu=False, out=None): data3 = fluid.layers.fill_constant(shape=[1, positive_2], dtype='float32', value=1.5) # data3=[1.5, 1.5] # attr shape is an Variable Tensor. - shape = fluid.layers.fill_constant([1,2], "int32", 2) # shape=[2,2] + shape = fluid.layers.fill_constant([2], "int32", 2) # shape=[2,2] data4 = fluid.layers.fill_constant(shape=shape, dtype='bool', value=True) # data4=[[True,True],[True,True]] # attr value is an Variable Tensor. val = fluid.layers.fill_constant([1], "float32", 2.0) # val=[2.0] data5 = fluid.layers.fill_constant(shape=[2,1], value=val, dtype='float32') #data5=[[2.0],[2.0]] """ - inputs = {} + attrs = {'force_cpu': force_cpu} - if isinstance(value, Variable): - inputs['ValueTensor'] = value - else: - attrs['value'] = float(value) + if not isinstance(value, Variable): if convert_dtype(dtype) in ['int64', 'int32']: attrs['str_value'] = str(int(value)) else: @@ -702,13 +701,19 @@ def fill_constant(shape, dtype, value, force_cpu=False, out=None): out.stop_gradient = True return out + helper = LayerHelper("fill_constant", **locals()) + inputs = {} + if isinstance(value, Variable): + inputs['ValueTensor'] = value + check_dtype(dtype, 'dtype', ['bool', 'float16', 'float32', 'float64', 'int32', 'int64'], 'fill_constant') check_type(shape, 'shape', (Variable, list, tuple), 'fill_constant') + if isinstance(shape, Variable): - check_variable_and_dtype(shape, 'shape', ['int32', 'int64'], - 'fill_constant') + check_dtype(shape.dtype, 'shape', ['int32', 'int64'], 'fill_constant') + if out is not None: check_variable_and_dtype(out, 'out', [convert_dtype(dtype)], 'fill_constant') @@ -1048,7 +1053,7 @@ def ones(shape, dtype, force_cpu=False): return fill_constant(value=1.0, **locals()) -def zeros(shape, dtype, force_cpu=False): +def zeros(shape, dtype, force_cpu=False, name=None): """ The OP creates a tensor of specified :attr:`shape` and :attr:`dtype`, and fills it with 0. Its :attr:`stop_gradient` will be set to True to stop gradient computation. @@ -1060,6 +1065,8 @@ def zeros(shape, dtype, force_cpu=False): force_cpu (bool, optional): Whether force to store the output tensor in CPU memory. If :attr:`force_cpu` is False, the output tensor will be stored in running device memory. Default: False. + name(str, optional): The default value is None. Normally there is no need for user to set this + property. For more information, please refer to :ref:`api_guide_Name`. Returns: Variable: A tensor of data type :attr:`dtype` with shape :attr:`shape` and all elements set to 0. @@ -1070,10 +1077,6 @@ def zeros(shape, dtype, force_cpu=False): import paddle.fluid as fluid data = fluid.layers.zeros(shape=[3, 2], dtype='float32') # [[0., 0.], [0., 0.], [0., 0.]] """ - check_type(shape, 'shape', (list, tuple), 'zeros') - check_dtype(dtype, 'create data type', - ['bool', 'float16', 'float32', 'float64', 'int32', 'int64'], - 'zeros') return fill_constant(value=0.0, **locals()) diff --git a/python/paddle/fluid/tests/unittests/test_fill_constant_op.py b/python/paddle/fluid/tests/unittests/test_fill_constant_op.py index 37d4e3e7abb..0bd3516e48d 100644 --- a/python/paddle/fluid/tests/unittests/test_fill_constant_op.py +++ b/python/paddle/fluid/tests/unittests/test_fill_constant_op.py @@ -22,8 +22,8 @@ import paddle import paddle.fluid.core as core from paddle.fluid.op import Operator import paddle.fluid as fluid -from paddle.fluid import compiler, Program, program_guard import numpy as np +from paddle.fluid import compiler, Program, program_guard # Situation 1: Attr(shape) is a list(without tensor) @@ -85,16 +85,14 @@ class TestFillConstantOp4(OpTest): class TestFillConstantOp5(unittest.TestCase): def test_errors(self): - with fluid.program_guard(fluid.Program()): - data = fluid.data(name="X", shape=[1], dtype="float32") - out = paddle.zeros(shape=[1], out=data, dtype="float32") + with program_guard(Program()): + out_np = np.zeros(shape=(1), dtype='float32') + out = paddle.zeros(shape=[1], dtype="float32") place = fluid.CPUPlace() exe = fluid.Executor(place) - result = exe.run(feed={"X": np.array( - [0.1], dtype="float32")}, - fetch_list=[data, out]) - self.assertEqual(result[0], result[1]) - with fluid.program_guard(fluid.Program()): + result = exe.run(fetch_list=[out]) + self.assertEqual((result == out_np).all(), True) + with program_guard(Program()): data = fluid.data(name="X", shape=[1], dtype="float32") out = paddle.ones(shape=[1], out=data, dtype="float32") place = fluid.CPUPlace() @@ -389,98 +387,5 @@ class TestFillConstantOpError(unittest.TestCase): self.assertRaises(TypeError, test_shape_tensor_list_dtype) -class ApiZerosTest(unittest.TestCase): - def test_out(self): - with fluid.program_guard(fluid.Program()): - zeros = paddle.zeros(shape=[10], dtype="float64") - place = fluid.CPUPlace() - exe = fluid.Executor(place) - result, = exe.run(fetch_list=[zeros]) - expected_result = np.zeros(10, dtype="float64") - self.assertEqual((result == expected_result).all(), True) - - with fluid.program_guard(fluid.Program()): - zeros = paddle.zeros(shape=[10], dtype="int64") - place = fluid.CPUPlace() - exe = fluid.Executor(place) - result, = exe.run(fetch_list=[zeros]) - expected_result = np.zeros(10, dtype="int64") - self.assertEqual((result == expected_result).all(), True) - - with fluid.program_guard(fluid.Program()): - zeros = paddle.zeros(shape=[10], dtype="int64", device="cpu") - place = fluid.CPUPlace() - exe = fluid.Executor(place) - result, = exe.run(fetch_list=[zeros]) - expected_result = np.zeros(10, dtype="int64") - self.assertEqual((result == expected_result).all(), True) - - -class ApiOnesTest(unittest.TestCase): - def test_out(self): - with fluid.program_guard(fluid.Program()): - ones = paddle.ones(shape=[10], dtype="float64") - place = fluid.CPUPlace() - exe = fluid.Executor(place) - result, = exe.run(fetch_list=[ones]) - expected_result = np.ones(10, dtype="float64") - self.assertEqual((result == expected_result).all(), True) - - with fluid.program_guard(fluid.Program()): - ones = paddle.ones(shape=[10], dtype="int64") - place = fluid.CPUPlace() - exe = fluid.Executor(place) - result, = exe.run(fetch_list=[ones]) - expected_result = np.ones(10, dtype="int64") - self.assertEqual((result == expected_result).all(), True) - - with fluid.program_guard(fluid.Program()): - ones = paddle.ones(shape=[10], dtype="int64", device="cpu") - place = fluid.CPUPlace() - exe = fluid.Executor(place) - result, = exe.run(fetch_list=[ones]) - expected_result = np.ones(10, dtype="int64") - self.assertEqual((result == expected_result).all(), True) - - -class ApiOnesZerosError(unittest.TestCase): - def test_errors(self): - def test_error1(): - with fluid.program_guard(fluid.Program()): - ones = paddle.ones(shape=10, dtype="int64", device="opu") - - self.assertRaises(ValueError, test_error1) - - def test_error2(): - with fluid.program_guard(fluid.Program()): - ones = paddle.ones(shape=10, dtype="int64", device="opu") - - self.assertRaises(ValueError, test_error2) - - def test_error3(): - with fluid.program_guard(fluid.Program()): - ones = fluid.layers.ones(shape=10, dtype="int64") - - self.assertRaises(TypeError, test_error3) - - def test_error4(): - with fluid.program_guard(fluid.Program()): - ones = fluid.layers.ones(shape=[10], dtype="int8") - - self.assertRaises(TypeError, test_error4) - - def test_error5(): - with fluid.program_guard(fluid.Program()): - ones = fluid.layers.zeros(shape=10, dtype="int64") - - self.assertRaises(TypeError, test_error5) - - def test_error6(): - with fluid.program_guard(fluid.Program()): - ones = fluid.layers.zeros(shape=[10], dtype="int8") - - self.assertRaises(TypeError, test_error6) - - if __name__ == "__main__": unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_full_op.py b/python/paddle/fluid/tests/unittests/test_full_op.py index 29d5be1ea42..01761b661e4 100644 --- a/python/paddle/fluid/tests/unittests/test_full_op.py +++ b/python/paddle/fluid/tests/unittests/test_full_op.py @@ -37,33 +37,19 @@ class TestFullAPI(unittest.TestCase): shape_tensor_int64 = fluid.data( name="shape_tensor_int64", shape=[2], dtype="int64") - out_1 = paddle.full( - shape=[1, 2], dtype="float32", fill_value=1.1, device='gpu') + out_1 = paddle.full(shape=[1, 2], dtype="float32", fill_value=1.1) out_2 = paddle.full( - shape=[1, positive_2_int32], - dtype="float32", - fill_value=1.1, - device='cpu') + shape=[1, positive_2_int32], dtype="float32", fill_value=1.1) out_3 = paddle.full( - shape=[1, positive_2_int64], - dtype="float32", - fill_value=1.1, - device='gpu') + shape=[1, positive_2_int64], dtype="float32", fill_value=1.1) out_4 = paddle.full( - shape=shape_tensor_int32, - dtype="float32", - fill_value=1.2, - out=out_3) + shape=shape_tensor_int32, dtype="float32", fill_value=1.2) out_5 = paddle.full( - shape=shape_tensor_int64, - dtype="float32", - fill_value=1.1, - device='gpu', - stop_gradient=False) + shape=shape_tensor_int64, dtype="float32", fill_value=1.1) out_6 = paddle.full( shape=shape_tensor_int64, dtype=np.float32, fill_value=1.1) @@ -83,7 +69,7 @@ class TestFullAPI(unittest.TestCase): assert np.array_equal(res_1, np.full([1, 2], 1.1, dtype="float32")) assert np.array_equal(res_2, np.full([1, 2], 1.1, dtype="float32")) - assert np.array_equal(res_3, np.full([1, 2], 1.2, dtype="float32")) + assert np.array_equal(res_3, np.full([1, 2], 1.1, dtype="float32")) assert np.array_equal(res_4, np.full([1, 2], 1.2, dtype="float32")) assert np.array_equal(res_5, np.full([1, 2], 1.1, dtype="float32")) assert np.array_equal(res_6, np.full([1, 2], 1.1, dtype="float32")) @@ -94,28 +80,11 @@ class TestFullOpError(unittest.TestCase): def test_errors(self): with program_guard(Program(), Program()): #for ci coverage - x1 = fluid.layers.data(name='x1', shape=[1], dtype="int16") - x2 = np.random.randn(1, 2).astype('int32') self.assertRaises( ValueError, paddle.full, shape=[1], fill_value=5, dtype='uint4') - self.assertRaises( - TypeError, - paddle.full, - shape=[1], - fill_value=5, - dtype='int32', - out=x2) - self.assertRaises( - TypeError, - paddle.full, - shape=[1], - fill_value=5, - dtype='int16', - out=x1) # The argument dtype of full must be one of bool, float16, #float32, float64, int32 or int64 - x2 = fluid.layers.data(name='x2', shape=[1], dtype="int32") self.assertRaises( TypeError, paddle.full, shape=[1], fill_value=5, dtype='uint8') diff --git a/python/paddle/fluid/tests/unittests/test_ones_op.py b/python/paddle/fluid/tests/unittests/test_ones_op.py new file mode 100644 index 00000000000..6061bfcff44 --- /dev/null +++ b/python/paddle/fluid/tests/unittests/test_ones_op.py @@ -0,0 +1,83 @@ +# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved. +# +# 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 print_function + +import unittest +import numpy as np +from op_test import OpTest + +import paddle +import paddle.fluid.core as core +from paddle.fluid.op import Operator +import paddle.fluid as fluid +import numpy as np + + +class ApiOnesTest(unittest.TestCase): + def test_out(self): + with fluid.program_guard(fluid.Program()): + ones = paddle.ones(shape=[10], dtype="float64") + place = fluid.CPUPlace() + exe = fluid.Executor(place) + result, = exe.run(fetch_list=[ones]) + expected_result = np.ones(10, dtype="float64") + self.assertEqual((result == expected_result).all(), True) + + with fluid.program_guard(fluid.Program()): + ones = paddle.ones(shape=[10], dtype="int64") + place = fluid.CPUPlace() + exe = fluid.Executor(place) + result, = exe.run(fetch_list=[ones]) + expected_result = np.ones(10, dtype="int64") + self.assertEqual((result == expected_result).all(), True) + + with fluid.program_guard(fluid.Program()): + ones = paddle.ones(shape=[10], dtype="int64", device="cpu") + place = fluid.CPUPlace() + exe = fluid.Executor(place) + result, = exe.run(fetch_list=[ones]) + expected_result = np.ones(10, dtype="int64") + self.assertEqual((result == expected_result).all(), True) + + +class ApiOnesZerosError(unittest.TestCase): + def test_errors(self): + def test_error1(): + with fluid.program_guard(fluid.Program()): + ones = paddle.ones(shape=10, dtype="int64", device="opu") + + self.assertRaises(ValueError, test_error1) + + def test_error2(): + with fluid.program_guard(fluid.Program()): + ones = paddle.ones(shape=10, dtype="int64", device="opu") + + self.assertRaises(ValueError, test_error2) + + def test_error3(): + with fluid.program_guard(fluid.Program()): + ones = fluid.layers.ones(shape=10, dtype="int64") + + self.assertRaises(TypeError, test_error3) + + def test_error4(): + with fluid.program_guard(fluid.Program()): + ones = fluid.layers.ones(shape=[10], dtype="int8") + + self.assertRaises(TypeError, test_error4) + + +if __name__ == "__main__": + unittest.main() diff --git a/python/paddle/fluid/tests/unittests/test_zeros_op.py b/python/paddle/fluid/tests/unittests/test_zeros_op.py index 6ce39cd6376..b7f7d934183 100644 --- a/python/paddle/fluid/tests/unittests/test_zeros_op.py +++ b/python/paddle/fluid/tests/unittests/test_zeros_op.py @@ -18,6 +18,7 @@ import unittest import numpy as np from op_test import OpTest +import paddle import paddle.fluid.core as core from paddle.fluid.op import Operator import paddle.fluid as fluid @@ -33,5 +34,47 @@ class TestZerosOpError(unittest.TestCase): self.assertRaises(TypeError, fluid.layers.zeros, shape, dtype) +class ApiZerosTest(unittest.TestCase): + def test_out(self): + with paddle.program_guard(fluid.Program()): + zeros = paddle.zeros(shape=[10], dtype="float64") + place = fluid.CPUPlace() + exe = fluid.Executor(place) + result, = exe.run(fetch_list=[zeros]) + expected_result = np.zeros(10, dtype="float64") + self.assertEqual((result == expected_result).all(), True) + + with paddle.program_guard(fluid.Program()): + zeros = paddle.zeros(shape=[10], dtype="int64") + place = fluid.CPUPlace() + exe = fluid.Executor(place) + result, = exe.run(fetch_list=[zeros]) + expected_result = np.zeros(10, dtype="int64") + self.assertEqual((result == expected_result).all(), True) + + with paddle.program_guard(fluid.Program()): + zeros = paddle.zeros(shape=[10], dtype="int64") + place = fluid.CPUPlace() + exe = fluid.Executor(place) + result, = exe.run(fetch_list=[zeros]) + expected_result = np.zeros(10, dtype="int64") + self.assertEqual((result == expected_result).all(), True) + + +class ApiZerosError(unittest.TestCase): + def test_errors(self): + def test_error1(): + with paddle.program_guard(fluid.Program()): + ones = fluid.layers.zeros(shape=10, dtype="int64") + + self.assertRaises(TypeError, test_error1) + + def test_error2(): + with paddle.program_guard(fluid.Program()): + ones = fluid.layers.zeros(shape=[10], dtype="int8") + + self.assertRaises(TypeError, test_error2) + + if __name__ == "__main__": unittest.main() diff --git a/python/paddle/tensor/creation.py b/python/paddle/tensor/creation.py index 36490731967..85f2e69681e 100644 --- a/python/paddle/tensor/creation.py +++ b/python/paddle/tensor/creation.py @@ -223,7 +223,7 @@ def ones_like(input, dtype=None, device=None, name=None): return out -def zeros(shape, dtype, out=None, device=None): +def zeros(shape, dtype=None, name=None): """ :alias_main: paddle.zeros :alias: paddle.zeros,paddle.tensor.zeros,paddle.tensor.creation.zeros @@ -232,14 +232,10 @@ def zeros(shape, dtype, out=None, device=None): Args: shape(tuple|list): Shape of output tensor. - dtype(np.dtype|core.VarDesc.VarType|str): Data type of output tensor, it supports - bool, float16, float32, float64, int32 and int64. - out(Variable, optional): Optional output which can be any created - Variable that meets the requirements to store the result of operation. - if out is None, a new Varibale will be create to store the result. - device(str, optional): Which device to run the operator. The :attr:`device` must be - None,'cpu', 'gpu'. If :attr:`device` is None, it will be choose the device that the user set in - the paddle program. Default value is False. + dtype(np.dtype|core.VarDesc.VarType|str, optional): Data type of output tensor, it supports + bool, float16, float32, float64, int32 and int64. Default: if None, the date type is float32. + name(str, optional): The default value is None. Normally there is no need for user to set this + property. For more information, please refer to :ref:`api_guide_Name`. Returns: Variable: A tensor of data type :attr:`dtype` with shape :attr:`shape` and all elements set to 0. @@ -248,21 +244,14 @@ def zeros(shape, dtype, out=None, device=None): .. code-block:: python import paddle + + paddle.enable_imperative() # Now we are in imperative mode data = paddle.zeros(shape=[3, 2], dtype='float32') # [[0., 0.], [0., 0.], [0., 0.]] - data = paddle.zeros(shape=[2, 2], dtype='float32', device='cpu') # [[0., 0.], [0., 0.]] + data = paddle.zeros(shape=[2, 2], dtype='int32', name='zeros') # [[0, 0], [0, 0]] """ - check_dtype(dtype, 'create data type', - ['bool', 'float16', 'float32', 'float64', 'int32', 'int64'], - 'zeros') - if device is not None: - if device not in ['cpu', 'gpu']: - raise ValueError( - "The value of 'device' in zeros_op must be cpu or gpu, but received %s." - % (device)) - with fluid.device_guard(device): - return fill_constant(value=0.0, shape=shape, dtype=dtype, out=out) - - return fill_constant(value=0.0, shape=shape, dtype=dtype, out=out) + if dtype is None: + dtype = 'float32' + return fill_constant(value=0.0, shape=shape, dtype=dtype, name=name) def zeros_like(input, dtype=None, device=None, name=None): @@ -398,13 +387,7 @@ def eye(num_rows, return out -def full(shape, - fill_value, - out=None, - dtype=None, - device=None, - stop_gradient=True, - name=None): +def full(shape, fill_value, dtype=None, name=None): """ :alias_main: paddle.full :alias: paddle.full,paddle.tensor.full,paddle.tensor.creation.full @@ -418,17 +401,9 @@ def full(shape, If ``shape`` is an Variable, it should be an 1-D Tensor . fill_value(bool|float16|float32|float64|int32|int64|Variable): The constant value used to initialize the Tensor to be created. If fill_value is an Variable, it must be an 1-D Tensor. - out(Variable, optional): Optional output which can be any created - Variable that meets the requirements to store the result of operation. - if out is None, a new Varibale will be create to store the result. dtype(np.dtype|core.VarDesc.VarType|str, optional): Data type of the output tensor which can be float16, float32, float64, int32, int64, if dytpe is `None`, the data type of created tensor is `float32` - device(str, optional): On which device to run this Op. The :attr:`device` must be - None, 'cpu' or 'gpu'. If :attr:`device` is None, the device that the user set in - the paddle program will be chosen. Default value is None. - stop_gradient(bool, optional): Indicating if we stop gradient from current(out) Variable, - default value is True. name(str, optional): The default value is None. Normally there is no need for user to set this property. For more information, please refer to :ref:`api_guide_Name`. @@ -437,28 +412,26 @@ def full(shape, Raises: TypeError: The `dtype` must be one of None, bool, float16, float32, float64, int32 and int64. - TypeError: The `out` must be a Variable. TypeError: The `shape` must be one of Variable, list tuple. Examples: .. code-block:: python import paddle - import paddle.fluid as fluid + paddle.enable_imperative() # Now we are in imperative mode data1 = paddle.full(shape=[2,1], fill_value=0, dtype='int64') # data1=[[0],[0]] - data2 = paddle.full(shape=[2,1], fill_value=5, dtype='int64', device='gpu') # data2=[[5],[5]] # attr shape is a list which contains Variable Tensor. - positive_2 = fluid.layers.fill_constant([1], "int32", 2) + positive_2 = paddle.fill_constant([1], "int32", 2) data3 = paddle.full(shape=[1, positive_2], dtype='float32', fill_value=1.5) # data3=[1.5, 1.5] # attr shape is an Variable Tensor. - shape = fluid.layers.fill_constant([1,2], "int32", 2) # shape=[2,2] + shape = paddle.fill_constant([2], "int32", 2) # shape=[2,2] data4 = paddle.full(shape=shape, dtype='bool', fill_value=True) # data4=[[True,True],[True,True]] # attr value is an Variable Tensor. - val = fluid.layers.fill_constant([1], "float32", 2.0) # val=[2.0] + val = paddle.fill_constant([1], "float32", 2.0) # val=[2.0] data5 = paddle.full(shape=[2,1], fill_value=val, dtype='float32') #data5=[[2.0],[2.0]] """ @@ -467,21 +440,7 @@ def full(shape, if dtype is None: dtype = 'float32' - check_dtype(dtype, 'create data type', - ['bool', 'float16', 'float32', 'float64', 'int32', 'int64'], - 'full') - check_type(shape, 'shape', (Variable, list, tuple), 'full') - if out is not None: - check_type(out, 'out', (Variable), 'full') - - if out is None: - out = helper.create_variable_for_type_inference(dtype=dtype) - - out.stop_gradient = stop_gradient - - with device_guard(device): - out = fill_constant(shape=shape, dtype=dtype, value=fill_value, out=out) - return out + return fill_constant(shape=shape, dtype=dtype, value=fill_value, name=name) def arange(start, end, step=1, dtype=None, name=None): -- GitLab