From 5f2c0e7e953002552229f6a2737700473f975433 Mon Sep 17 00:00:00 2001 From: lilong12 Date: Fri, 21 Aug 2020 14:37:52 +0800 Subject: [PATCH] [2.0 api] fix the example codes in doc strings (#26428) * fix the example codes, test=develop --- .../tests/unittests/test_expand_as_v2_op.py | 13 +++++- .../fluid/tests/unittests/test_tile_op.py | 10 +++++ python/paddle/tensor/manipulation.py | 45 +++++++++++-------- 3 files changed, 49 insertions(+), 19 deletions(-) diff --git a/python/paddle/fluid/tests/unittests/test_expand_as_v2_op.py b/python/paddle/fluid/tests/unittests/test_expand_as_v2_op.py index 0ccb725870c..4bc6bf3744f 100755 --- a/python/paddle/fluid/tests/unittests/test_expand_as_v2_op.py +++ b/python/paddle/fluid/tests/unittests/test_expand_as_v2_op.py @@ -93,8 +93,19 @@ class TestExpandAsOpRank4(OpTest): self.check_grad(['X'], 'Out') +class TestExpandAsV2Error(unittest.TestCase): + def test_errors(self): + with fluid.program_guard(fluid.Program(), fluid.Program()): + x1 = fluid.layers.data(name='x1', shape=[4], dtype="uint8") + x2 = fluid.layers.data(name='x2', shape=[4], dtype="int32") + self.assertRaises(TypeError, paddle.tensor.expand_as, x1, x2) + x3 = fluid.layers.data(name='x3', shape=[4], dtype="bool") + x3.stop_gradient = False + self.assertRaises(ValueError, paddle.tensor.expand_as, x3, x2) + + # Test python API -class TestExpandAPI(unittest.TestCase): +class TestExpandAsV2API(unittest.TestCase): def test_api(self): input1 = np.random.random([12, 14]).astype("float32") input2 = np.random.random([2, 12, 14]).astype("float32") diff --git a/python/paddle/fluid/tests/unittests/test_tile_op.py b/python/paddle/fluid/tests/unittests/test_tile_op.py index 73e6ff5dbd6..5aaf3199344 100644 --- a/python/paddle/fluid/tests/unittests/test_tile_op.py +++ b/python/paddle/fluid/tests/unittests/test_tile_op.py @@ -215,6 +215,16 @@ class TestTileError(unittest.TestCase): self.assertRaises(ValueError, paddle.tile, x3, repeat_times) +class TestTileAPIStatic(unittest.TestCase): + def test_api(self): + with program_guard(Program(), Program()): + repeat_times = [2, 2] + x1 = fluid.layers.data(name='x1', shape=[4], dtype="int32") + out = paddle.tile(x1, repeat_times) + positive_2 = fluid.layers.fill_constant([1], dtype="int32", value=2) + out2 = paddle.tile(x1, repeat_times=[positive_2, 2]) + + # Test python API class TestTileAPI(unittest.TestCase): def test_api(self): diff --git a/python/paddle/tensor/manipulation.py b/python/paddle/tensor/manipulation.py index 99281656eff..88342c89da7 100644 --- a/python/paddle/tensor/manipulation.py +++ b/python/paddle/tensor/manipulation.py @@ -841,7 +841,7 @@ def tile(x, repeat_times, name=None): """ Construct a new Tensor by repeating ``x`` the number of times given by ``repeat_times``. - After tiling, the number of elements of the i'th dimension of the output is equal to ``x.dims[i] * repeat_times[i]``. + After tiling, the value of the i'th dimension of the output is equal to ``x.shape[i]*repeat_times[i]``. Both the number of dimensions of ``x`` and the number of elements in ``repeat_times`` should be less than or equal to 6. @@ -862,9 +862,9 @@ def tile(x, repeat_times, name=None): paddle.disable_static() np_data = np.array([1, 2, 3]).astype('int32') - data = paddle.to_variable(np_data) + data = paddle.to_tensor(np_data) out = paddle.tile(data, repeat_times=[2, 1]) - np_out = out1.numpy() + np_out = out.numpy() # [[1, 2, 3], [1, 2, 3]] out = paddle.tile(data, repeat_times=[2, 2]) @@ -872,7 +872,7 @@ def tile(x, repeat_times, name=None): # [[1, 2, 3, 1, 2, 3], [1, 2, 3, 1, 2, 3]] np_repeat_times = np.array([2, 1]).astype("int32") - repeat_times = paddle.to_variable(np_repeat_times) + repeat_times = paddle.to_tensor(np_repeat_times) out = paddle.tile(data, repeat_times=repeat_times) np_out = out.numpy() # [[1, 2, 3], [1, 2, 3]] @@ -884,9 +884,12 @@ def tile(x, repeat_times, name=None): raise ValueError( "When the date type is bool for the input 'x' of tile op, you " "must set its stop_gradient to be True by " - "some_var.stop_gradient == True supporting some_var as the input.") + "some_var.stop_gradient == True supporting some_var is the input.") + + if in_dygraph_mode(): + return core.ops.tile(x, 'repeat_times', repeat_times) - helper = LayerHelper('tile', input=x, **locals()) + helper = LayerHelper('tile', **locals()) inputs = {"X": [x]} attrs = {} @@ -928,7 +931,7 @@ def expand_as(x, y, name=None): Args: x (Tensor): The input tensor, its data type is bool, float32, float64, int32 or int64. - y (Tensor): The input tensor gives the shape that ``x`` to expand to. + y (Tensor): The input tensor that gives the shape to expand to. 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: @@ -942,10 +945,10 @@ def expand_as(x, y, name=None): paddle.disable_static() - np_data_x = np.array([1, 2, 3]).astype=('int32) - np_data_y = np.array([[1, 2, 3], [4, 5, 6]]).astype=('int32) - data_x = paddle.to_variable(np_data_x) - data_y = paddle.to_variable(np_data_y) + np_data_x = np.array([1, 2, 3]).astype('int32') + np_data_y = np.array([[1, 2, 3], [4, 5, 6]]).astype('int32') + data_x = paddle.to_tensor(np_data_x) + data_y = paddle.to_tensor(np_data_y) out = paddle.expand_as(data_x, data_y) np_out = out.numpy() # [[1, 2, 3], [1, 2, 3]] @@ -962,7 +965,10 @@ def expand_as(x, y, name=None): "some_var as the input 'x'.") inputs = {"X": [x], "target_tensor": [y]} - helper = LayerHelper('expand_as', input=x, **locals()) + if in_dygraph_mode(): + return core.ops.expand_as_v2(x, y) + + helper = LayerHelper('expand_as', **locals()) dtype = helper.input_dtype(input_param_name='x') out = helper.create_variable_for_type_inference(dtype) helper.append_op(type='expand_as_v2', inputs=inputs, outputs={'Out': out}) @@ -994,16 +1000,16 @@ def expand(x, shape, name=None): import paddle paddle.disable_static() - np_data = np.array([1, 2, 3]).astype=('int32) - data = paddle.to_variable(np_data) + np_data = np.array([1, 2, 3]).astype('int32') + data = paddle.to_tensor(np_data) out = paddle.expand(data, shape=[2, 3]) out = out.numpy() # [[1, 2, 3], [1, 2, 3]] - np_shape = np.array([2, 3]).astype=('int32) - shape = paddle.to_variable(np_shape) + np_shape = np.array([2, 3]).astype('int32') + shape = paddle.to_tensor(np_shape) out = paddle.expand(data, shape=shape) - out = out.numpy + out = out.numpy() # [[1, 2, 3], [1, 2, 3]] """ check_variable_and_dtype( @@ -1018,7 +1024,10 @@ def expand(x, shape, name=None): "some_var.stop_gradient = True, supporting " "some_var as the input.") - helper = LayerHelper('expand', input=x, **locals()) + if in_dygraph_mode(): + return core.ops.expand_v2(x, 'shape', shape) + + helper = LayerHelper('expand', **locals()) def get_attr_expand_shape(list_expand_shape): attrs_expand_shape = [] -- GitLab