diff --git a/python/paddle/fluid/tests/unittests/test_greater_equal_op.py b/python/paddle/fluid/tests/unittests/test_greater_equal_op.py new file mode 100644 index 0000000000000000000000000000000000000000..673000d1889bdfbe9941760027874544c1492d5a --- /dev/null +++ b/python/paddle/fluid/tests/unittests/test_greater_equal_op.py @@ -0,0 +1,41 @@ +# 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. + + +import unittest + +import numpy as np + +import paddle +import paddle.fluid.core as core +import paddle.static as static + + +class Test_Greater_Equal_Op_Fp16(unittest.TestCase): + def test_api_fp16(self): + paddle.enable_static() + with static.program_guard(static.Program(), static.Program()): + label = paddle.to_tensor([3, 3], dtype="float16") + limit = paddle.to_tensor([3, 2], dtype="float16") + out = paddle.greater_equal(x=label, y=limit) + if core.is_compiled_with_cuda(): + place = paddle.CUDAPlace(0) + exe = static.Executor(place) + (res,) = exe.run(fetch_list=[out]) + self.assertEqual((res == np.array([True, True])).all(), True) + + +if __name__ == '__main__': + paddle.enable_static() + unittest.main() diff --git a/python/paddle/tensor/logic.py b/python/paddle/tensor/logic.py index 0ca0935c88a560dfea19017056e10a92e684a805..524d3dd0cb49b0563acdbd47761c218c251f8ac9 100644 --- a/python/paddle/tensor/logic.py +++ b/python/paddle/tensor/logic.py @@ -495,8 +495,8 @@ def greater_equal(x, y, name=None): The output has no gradient. Args: - x(Tensor): First input to compare which is N-D tensor. The input data type should be bool, float32, float64, int32, int64. - y(Tensor): Second input to compare which is N-D tensor. The input data type should be bool, float32, float64, int32, int64. + x(Tensor): First input to compare which is N-D tensor. The input data type should be bool, float16, float32, float64, int32, int64. + y(Tensor): Second input to compare which is N-D tensor. The input data type should be bool, float16, float32, float64, int32, int64. 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: @@ -518,13 +518,13 @@ def greater_equal(x, y, name=None): check_variable_and_dtype( x, "x", - ["bool", "float32", "float64", "int32", "int64"], + ["bool", "float16", "float32", "float64", "int32", "int64"], "greater_equal", ) check_variable_and_dtype( y, "y", - ["bool", "float32", "float64", "int32", "int64"], + ["bool", "float16", "float32", "float64", "int32", "int64"], "greater_equal", ) helper = LayerHelper("greater_equal", **locals())