diff --git a/python/paddle/fluid/tests/unittests/test_gaussian_random_op.py b/python/paddle/fluid/tests/unittests/test_gaussian_random_op.py index 71665600bc73a6725bbe46a7def9518c8ab1ee50..dddc6811ef08bdf8504cb6b4fe09813336875b10 100644 --- a/python/paddle/fluid/tests/unittests/test_gaussian_random_op.py +++ b/python/paddle/fluid/tests/unittests/test_gaussian_random_op.py @@ -239,24 +239,24 @@ class TestGaussianRandomAPI(unittest.TestCase): def test_default_dtype(self): paddle.disable_static() - def test_default_fp_16(): + def test_default_fp16(): paddle.framework.set_default_dtype('float16') paddle.tensor.random.gaussian([2, 3]) - self.assertRaises(TypeError, test_default_fp_16) + self.assertRaises(TypeError, test_default_fp16) - def test_default_fp_32(): + def test_default_fp32(): paddle.framework.set_default_dtype('float32') out = paddle.tensor.random.gaussian([2, 3]) self.assertEqual(out.dtype, fluid.core.VarDesc.VarType.FP32) - def test_default_fp_64(): + def test_default_fp64(): paddle.framework.set_default_dtype('float64') out = paddle.tensor.random.gaussian([2, 3]) self.assertEqual(out.dtype, fluid.core.VarDesc.VarType.FP64) - test_default_fp_64() - test_default_fp_32() + test_default_fp64() + test_default_fp32() paddle.enable_static() @@ -265,24 +265,24 @@ class TestStandardNormalDtype(unittest.TestCase): def test_default_dtype(self): paddle.disable_static() - def test_default_fp_16(): + def test_default_fp16(): paddle.framework.set_default_dtype('float16') paddle.tensor.random.standard_normal([2, 3]) - self.assertRaises(TypeError, test_default_fp_16) + self.assertRaises(TypeError, test_default_fp16) - def test_default_fp_32(): + def test_default_fp32(): paddle.framework.set_default_dtype('float32') out = paddle.tensor.random.standard_normal([2, 3]) self.assertEqual(out.dtype, fluid.core.VarDesc.VarType.FP32) - def test_default_fp_64(): + def test_default_fp64(): paddle.framework.set_default_dtype('float64') out = paddle.tensor.random.standard_normal([2, 3]) self.assertEqual(out.dtype, fluid.core.VarDesc.VarType.FP64) - test_default_fp_64() - test_default_fp_32() + test_default_fp64() + test_default_fp32() paddle.enable_static() diff --git a/python/paddle/fluid/tests/unittests/test_rand_op.py b/python/paddle/fluid/tests/unittests/test_rand_op.py index 1eceeaadfec651ade5031ddc7e6a012244050e84..4b8fe8c7e4786417de2f80dbb9953530781f9189 100644 --- a/python/paddle/fluid/tests/unittests/test_rand_op.py +++ b/python/paddle/fluid/tests/unittests/test_rand_op.py @@ -120,24 +120,24 @@ class TestRandDtype(unittest.TestCase): def test_default_dtype(self): paddle.disable_static() - def test_default_fp_16(): + def test_default_fp16(): paddle.framework.set_default_dtype('float16') paddle.tensor.random.rand([2, 3]) - self.assertRaises(TypeError, test_default_fp_16) + self.assertRaises(TypeError, test_default_fp16) - def test_default_fp_32(): + def test_default_fp32(): paddle.framework.set_default_dtype('float32') out = paddle.tensor.random.rand([2, 3]) self.assertEqual(out.dtype, fluid.core.VarDesc.VarType.FP32) - def test_default_fp_64(): + def test_default_fp64(): paddle.framework.set_default_dtype('float64') out = paddle.tensor.random.rand([2, 3]) self.assertEqual(out.dtype, fluid.core.VarDesc.VarType.FP64) - test_default_fp_64() - test_default_fp_32() + test_default_fp64() + test_default_fp32() paddle.enable_static() diff --git a/python/paddle/fluid/tests/unittests/test_uniform_random_op.py b/python/paddle/fluid/tests/unittests/test_uniform_random_op.py index bbe6f7fb3db2557cdc3043261a086b0e0c26ff9d..5ecf25c53b794f07e298b986eff5700698b8bff7 100644 --- a/python/paddle/fluid/tests/unittests/test_uniform_random_op.py +++ b/python/paddle/fluid/tests/unittests/test_uniform_random_op.py @@ -540,24 +540,24 @@ class TestUniformDtype(unittest.TestCase): def test_default_dtype(self): paddle.disable_static() - def test_default_fp_16(): + def test_default_fp16(): paddle.framework.set_default_dtype('float16') paddle.tensor.random.uniform([2, 3]) - self.assertRaises(TypeError, test_default_fp_16) + self.assertRaises(TypeError, test_default_fp16) - def test_default_fp_32(): + def test_default_fp32(): paddle.framework.set_default_dtype('float32') out = paddle.tensor.random.uniform([2, 3]) self.assertEqual(out.dtype, fluid.core.VarDesc.VarType.FP32) - def test_default_fp_64(): + def test_default_fp64(): paddle.framework.set_default_dtype('float64') out = paddle.tensor.random.uniform([2, 3]) self.assertEqual(out.dtype, fluid.core.VarDesc.VarType.FP64) - test_default_fp_64() - test_default_fp_32() + test_default_fp64() + test_default_fp32() paddle.enable_static() diff --git a/python/paddle/tensor/random.py b/python/paddle/tensor/random.py index 7ce3475cddde3b86f69aa18af767bc7a813edbc7..19ac4afcbec8acd384072aef8fb615f80d9de16a 100644 --- a/python/paddle/tensor/random.py +++ b/python/paddle/tensor/random.py @@ -393,8 +393,8 @@ def uniform(shape, dtype=None, min=-1.0, max=1.0, seed=0, name=None): dtype = paddle.framework.get_default_dtype() if dtype not in ['float32', 'float64']: raise TypeError( - "uniform only supports [float32, float64], but the default dtype is %s" - % dtype) + "uniform/rand only supports [float32, float64], but the default dtype is {}". + format(dtype)) if not isinstance(dtype, core.VarDesc.VarType): dtype = convert_np_dtype_to_dtype_(dtype) @@ -405,15 +405,15 @@ def uniform(shape, dtype=None, min=-1.0, max=1.0, seed=0, name=None): float(min), 'max', float(max), 'seed', seed, 'dtype', dtype) - check_type(shape, 'shape', (list, tuple, Variable), 'uniform_random/rand') - check_dtype(dtype, 'dtype', ('float32', 'float64'), 'uniform_random/rand') + check_type(shape, 'shape', (list, tuple, Variable), 'uniform/rand') + check_dtype(dtype, 'dtype', ('float32', 'float64'), 'uniform/rand') inputs = dict() attrs = {'seed': seed, 'min': min, 'max': max, 'dtype': dtype} utils.get_shape_tensor_inputs( - inputs=inputs, attrs=attrs, shape=shape, op_type='uniform_random/rand') + inputs=inputs, attrs=attrs, shape=shape, op_type='uniform/rand') - helper = LayerHelper("uniform_random", **locals()) + helper = LayerHelper("uniform", **locals()) out = helper.create_variable_for_type_inference(dtype) helper.append_op( type="uniform_random", inputs=inputs, attrs=attrs,