From 90cf2299960ba2409a4b87b58a4070020bcaba46 Mon Sep 17 00:00:00 2001 From: zlsh80826 Date: Tue, 14 Jun 2022 09:17:14 +0800 Subject: [PATCH] Fix numpy 1.20+ deprecation warnings (#42929) * Replace np.bool/np.bool8 with np.bool_ * Replace np.object with np.object_ * Replace np.complex with np.complex128 * Replace np.float with np.float64 * Replace np.int with np.int_ * Rerun pre-commit for newer pre-commit configuration * Use builtin bool instead of np.bool_ based on the context --- python/paddle/distributed/fleet/base/fleet_base.py | 4 ++-- .../meta_parallel/sharding/group_sharded_utils.py | 4 ++-- .../fleet/meta_parallel/sharding/sharding_utils.py | 4 ++-- python/paddle/fluid/data_feeder.py | 2 +- python/paddle/fluid/dygraph/amp/loss_scaler.py | 6 +++--- python/paddle/fluid/executor.py | 2 +- python/paddle/fluid/framework.py | 2 +- python/paddle/fluid/layers/nn.py | 8 ++++---- python/paddle/fluid/reader.py | 2 +- python/paddle/fluid/tests/unittests/fft/test_fft.py | 10 +++++----- .../unittests/fft/test_fft_with_static_graph.py | 12 ++++++------ .../fluid/tests/unittests/ipu/test_assign_op_ipu.py | 2 +- .../unittests/mkldnn/test_mul_int8_mkldnn_op.py | 4 ++-- .../unittests/mkldnn/test_softmax_bf16_mkldnn_op.py | 2 +- .../tests/unittests/npu/test_box_coder_op_npu.py | 2 +- .../unittests/npu/test_density_prior_box_op_npu.py | 2 +- .../unittests/npu/test_fill_zeros_like_op_npu.py | 2 +- .../tests/unittests/npu/test_prior_box_op_npu.py | 4 ++-- .../tests/unittests/npu/test_reduce_max_op_npu.py | 2 +- .../tests/unittests/npu/test_reduce_min_op_npu.py | 2 +- .../tests/unittests/npu/test_reduce_prod_op_npu.py | 3 ++- .../fluid/tests/unittests/npu/test_size_op_npu.py | 2 +- .../tests/unittests/npu/test_tril_triu_op_npu.py | 2 +- .../npu/test_update_loss_scaling_min_op_npu.py | 2 +- .../unittests/npu/test_update_loss_scaling_op_npu.py | 4 ++-- python/paddle/fluid/tests/unittests/op_test.py | 2 +- .../paddle/fluid/tests/unittests/test_assign_op.py | 2 +- .../fluid/tests/unittests/test_bipartite_match_op.py | 4 ++-- .../fluid/tests/unittests/test_box_coder_op.py | 2 +- .../paddle/fluid/tests/unittests/test_compare_op.py | 8 ++++---- .../tests/unittests/test_density_prior_box_op.py | 2 +- .../tests/unittests/test_fuse_gemm_epilogue_pass.py | 2 +- .../unittests/test_fused_multi_transformer_op.py | 4 ++-- .../tests/unittests/test_generate_mask_labels_op.py | 6 +++--- python/paddle/fluid/tests/unittests/test_kron_op.py | 4 ++-- .../paddle/fluid/tests/unittests/test_ones_like.py | 6 +++--- .../fluid/tests/unittests/test_prior_box_op.py | 4 ++-- .../paddle/fluid/tests/unittests/test_reduce_op.py | 4 ++-- python/paddle/fluid/tests/unittests/test_signal.py | 6 +++--- .../tests/unittests/test_update_loss_scaling_op.py | 4 ++-- .../fluid/tests/unittests/test_zeros_like_op.py | 6 +++--- .../fluid/tests/unittests/xpu/test_compare_op_xpu.py | 8 ++++---- .../tests/unittests/xpu/test_prior_box_op_xpu.py | 5 +++-- .../unittests/xpu/test_update_loss_scaling_op_xpu.py | 4 ++-- python/paddle/nn/layer/conv.py | 2 +- python/paddle/tensor/creation.py | 2 +- python/paddle/tensor/linalg.py | 2 +- python/paddle/tensor/logic.py | 8 ++++---- 48 files changed, 95 insertions(+), 93 deletions(-) diff --git a/python/paddle/distributed/fleet/base/fleet_base.py b/python/paddle/distributed/fleet/base/fleet_base.py index 762b961da53..d41f0fbb845 100755 --- a/python/paddle/distributed/fleet/base/fleet_base.py +++ b/python/paddle/distributed/fleet/base/fleet_base.py @@ -1811,8 +1811,8 @@ class Fleet(object): if (param._grad_ivar() is not None) and ( param._grad_ivar().dtype == core.VarDesc.VarType.FP32) ] - temp_found_inf_fp16 = to_variable(np.array([0]).astype(np.bool)) - temp_found_inf_fp32 = to_variable(np.array([0]).astype(np.bool)) + temp_found_inf_fp16 = to_variable(np.array([0]).astype(np.bool_)) + temp_found_inf_fp32 = to_variable(np.array([0]).astype(np.bool_)) if len(param_grads_fp16): _C_ops.check_finite_and_unscale(param_grads_fp16, self._scale, param_grads_fp16, diff --git a/python/paddle/distributed/fleet/meta_parallel/sharding/group_sharded_utils.py b/python/paddle/distributed/fleet/meta_parallel/sharding/group_sharded_utils.py index b1e0f6cc130..fcbbadbe121 100644 --- a/python/paddle/distributed/fleet/meta_parallel/sharding/group_sharded_utils.py +++ b/python/paddle/distributed/fleet/meta_parallel/sharding/group_sharded_utils.py @@ -200,8 +200,8 @@ def GroupShardedScaler(scaler): else: param_grads_fp32.append(param.grad) - temp_found_inf_fp16 = to_variable(np.array([0]).astype(np.bool)) - temp_found_inf_fp32 = to_variable(np.array([0]).astype(np.bool)) + temp_found_inf_fp16 = to_variable(np.array([0]).astype(np.bool_)) + temp_found_inf_fp32 = to_variable(np.array([0]).astype(np.bool_)) device = "cpu" if optimizer.offload else "gpu" dev_id = 0 if device == "cpu" else int( diff --git a/python/paddle/distributed/fleet/meta_parallel/sharding/sharding_utils.py b/python/paddle/distributed/fleet/meta_parallel/sharding/sharding_utils.py index ae98d4bdf7b..63e2b91b3d9 100644 --- a/python/paddle/distributed/fleet/meta_parallel/sharding/sharding_utils.py +++ b/python/paddle/distributed/fleet/meta_parallel/sharding/sharding_utils.py @@ -201,8 +201,8 @@ def ShardingScaler(scaler): else: param_grads_fp32.append(param.grad) - temp_found_inf_fp16 = to_variable(np.array([0]).astype(np.bool)) - temp_found_inf_fp32 = to_variable(np.array([0]).astype(np.bool)) + temp_found_inf_fp16 = to_variable(np.array([0]).astype(np.bool_)) + temp_found_inf_fp32 = to_variable(np.array([0]).astype(np.bool_)) device = "cpu" if optimizer.offload else "gpu" dev_id = 0 if device == "cpu" else int( diff --git a/python/paddle/fluid/data_feeder.py b/python/paddle/fluid/data_feeder.py index 30cfb9f4b85..876d4772462 100644 --- a/python/paddle/fluid/data_feeder.py +++ b/python/paddle/fluid/data_feeder.py @@ -49,7 +49,7 @@ def convert_dtype(dtype): return _PADDLE_DTYPE_2_NUMPY_DTYPE[dtype] elif isinstance(dtype, type): if dtype in [ - np.bool, np.float16, np.uint16, np.float32, np.float64, np.int8, + bool, np.float16, np.uint16, np.float32, np.float64, np.int8, np.int16, np.int32, np.int64, np.uint8, np.complex64, np.complex128 ]: diff --git a/python/paddle/fluid/dygraph/amp/loss_scaler.py b/python/paddle/fluid/dygraph/amp/loss_scaler.py index 9da69b1e45e..e1ae4ad9bc5 100644 --- a/python/paddle/fluid/dygraph/amp/loss_scaler.py +++ b/python/paddle/fluid/dygraph/amp/loss_scaler.py @@ -129,11 +129,11 @@ class AmpScaler(object): self._decr_count = 0 self._use_dynamic_loss_scaling = use_dynamic_loss_scaling - self._found_inf = to_variable(np.array([0]).astype(np.bool)) + self._found_inf = to_variable(np.array([0]).astype(np.bool_)) self._temp_found_inf_fp16 = to_variable( - np.array([0]).astype(np.bool)) + np.array([0]).astype(np.bool_)) self._temp_found_inf_fp32 = to_variable( - np.array([0]).astype(np.bool)) + np.array([0]).astype(np.bool_)) self._scale = to_variable( np.array([self._init_loss_scaling]).astype(np.float32)) self._cache_founf_inf = None diff --git a/python/paddle/fluid/executor.py b/python/paddle/fluid/executor.py index 0d4acf5fe6d..860b4e3f558 100755 --- a/python/paddle/fluid/executor.py +++ b/python/paddle/fluid/executor.py @@ -483,7 +483,7 @@ def _as_lodtensor(data, place, dtype=None): data = np.array([data]).astype(dtype) elif isinstance(data, (list, tuple)): data = np.array(data) - if data.dtype == np.object: + if data.dtype == np.object_: raise TypeError( "\n\tFaild to convert input data to a regular ndarray :\n\t* Usually " "this means the input data contains nested lists with different lengths. " diff --git a/python/paddle/fluid/framework.py b/python/paddle/fluid/framework.py index 44ef1ff5ae6..2412e300a77 100644 --- a/python/paddle/fluid/framework.py +++ b/python/paddle/fluid/framework.py @@ -1109,7 +1109,7 @@ def convert_np_dtype_to_dtype_(np_dtype): return core.VarDesc.VarType.INT16 elif dtype == np.int64: return core.VarDesc.VarType.INT64 - elif dtype == np.bool: + elif dtype == np.bool_: return core.VarDesc.VarType.BOOL elif dtype == np.uint16: # since there is still no support for bfloat16 in NumPy, diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index 2c3cb903d83..d7f0feb103c 100755 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -12860,8 +12860,8 @@ def logical_or(x, y, out=None, name=None): import paddle import numpy as np - x_data = np.array([True, False], dtype=np.bool).reshape(2, 1) - y_data = np.array([True, False, True, False], dtype=np.bool).reshape(2, 2) + x_data = np.array([True, False], dtype=np.bool_).reshape(2, 1) + y_data = np.array([True, False, True, False], dtype=np.bool_).reshape(2, 2) x = paddle.to_tensor(x_data) y = paddle.to_tensor(y_data) res = paddle.logical_or(x, y) @@ -12905,8 +12905,8 @@ def logical_xor(x, y, out=None, name=None): import paddle import numpy as np - x_data = np.array([True, False], dtype=np.bool).reshape([2, 1]) - y_data = np.array([True, False, True, False], dtype=np.bool).reshape([2, 2]) + x_data = np.array([True, False], dtype=np.bool_).reshape([2, 1]) + y_data = np.array([True, False, True, False], dtype=np.bool_).reshape([2, 2]) x = paddle.to_tensor(x_data) y = paddle.to_tensor(y_data) res = paddle.logical_xor(x, y) diff --git a/python/paddle/fluid/reader.py b/python/paddle/fluid/reader.py index ff299bcca9b..c590d69a621 100644 --- a/python/paddle/fluid/reader.py +++ b/python/paddle/fluid/reader.py @@ -145,7 +145,7 @@ class DataLoaderBase(object): @classmethod def _check_input_array(cls, item): arr = np.asarray(item) - if arr.dtype == np.object: + if arr.dtype == np.object_: raise TypeError( "\n\tFaild to convert input data to a regular ndarray :\n\t* Usually " "this means the input data contains nested lists with different lengths. " diff --git a/python/paddle/fluid/tests/unittests/fft/test_fft.py b/python/paddle/fluid/tests/unittests/fft/test_fft.py index a3c62323c2c..f386fdc9c34 100644 --- a/python/paddle/fluid/tests/unittests/fft/test_fft.py +++ b/python/paddle/fluid/tests/unittests/fft/test_fft.py @@ -44,8 +44,8 @@ def rand_x(dims=1, complex=False): shape = [np.random.randint(min_dim_len, max_dim_len) for i in range(dims)] if complex: - return np.random.randn(*shape).astype( - dtype) + 1.j * np.random.randn(*shape).astype(dtype) + return np.random.randn( + *shape).astype(dtype) + 1.j * np.random.randn(*shape).astype(dtype) else: return np.random.randn(*shape).astype(dtype) @@ -473,7 +473,7 @@ class TestIrfft2(unittest.TestCase): @parameterize((TEST_CASE_NAME, 'x', 'n', 'axis', 'norm', 'expect_exception'), [ ('test_bool_input', (np.random.randn(4, 4, 4) + 1j * np.random.randn(4, 4, 4)).astype( - np.bool8), None, -1, 'backward', NotImplementedError), + np.bool_), None, -1, 'backward', NotImplementedError), ('test_n_nagative', np.random.randn(4, 4, 4) + 1j * np.random.randn(4, 4, 4), -1, -1, 'backward', ValueError), ('test_n_zero', np.random.randn(4, 4) + 1j * np.random.randn(4, 4), 0, -1, @@ -543,7 +543,7 @@ class TestIrfftException(unittest.TestCase): (TEST_CASE_NAME, 'x', 'n', 'axis', 'norm', 'expect_exception'), [('test_bool_input', (np.random.randn(4, 4, 4) + 1j * np.random.randn(4, 4, 4)).astype( - np.bool8), None, (-2, -1), 'backward', NotImplementedError), + np.bool_), None, (-2, -1), 'backward', NotImplementedError), ('test_n_nagative', np.random.randn(4, 4, 4) + 1j * np.random.randn(4, 4, 4), (-1, -2), (-2, -1), 'backward', ValueError), @@ -625,7 +625,7 @@ class TestIrfft2Exception(unittest.TestCase): (TEST_CASE_NAME, 'x', 'n', 'axis', 'norm', 'expect_exception'), [('test_bool_input', (np.random.randn(4, 4, 4) + 1j * np.random.randn(4, 4, 4)).astype( - np.bool8), None, (-2, -1), 'backward', NotImplementedError), + np.bool_), None, (-2, -1), 'backward', NotImplementedError), ('test_n_nagative', np.random.randn(4, 4, 4) + 1j * np.random.randn(4, 4, 4), (-1, -2), (-2, -1), 'backward', ValueError), diff --git a/python/paddle/fluid/tests/unittests/fft/test_fft_with_static_graph.py b/python/paddle/fluid/tests/unittests/fft/test_fft_with_static_graph.py index ce0a623aea0..ddf47065bb0 100644 --- a/python/paddle/fluid/tests/unittests/fft/test_fft_with_static_graph.py +++ b/python/paddle/fluid/tests/unittests/fft/test_fft_with_static_graph.py @@ -370,7 +370,7 @@ class TestIrfft2(unittest.TestCase): 4), None, -1, 'backward', TypeError), ('test_bool_input', (np.random.randn(4, 4, 4) + 1j * np.random.randn(4, 4, 4)).astype( - np.bool8), None, -1, 'backward', TypeError), + np.bool_), None, -1, 'backward', TypeError), ('test_n_nagative', np.random.randn(4, 4, 4) + 1j * np.random.randn(4, 4, 4), -1, -1, 'backward', ValueError), ('test_n_zero', np.random.randn(4, 4) + 1j * np.random.randn(4, 4), 0, -1, @@ -406,7 +406,7 @@ class TestHfftException(unittest.TestCase): 4), None, -1, 'backward', TypeError), ('test_bool_input', (np.random.randn(4, 4, 4) + 1j * np.random.randn(4, 4, 4)).astype( - np.bool8), None, -1, 'backward', TypeError), + np.bool_), None, -1, 'backward', TypeError), ('test_n_nagative', np.random.randn(4, 4, 4) + 1j * np.random.randn(4, 4, 4), -1, -1, 'backward', ValueError), ('test_n_zero', np.random.randn(4, 4) + 1j * np.random.randn(4, 4), 0, -1, @@ -444,7 +444,7 @@ class TestIrfftException(unittest.TestCase): 4, 4, 4), None, None, 'backward', TypeError), ('test_bool_input', (np.random.randn(4, 4, 4) + 1j * np.random.randn(4, 4, 4)).astype( - np.bool8), None, (-2, -1), 'backward', TypeError), + np.bool_), None, (-2, -1), 'backward', TypeError), ('test_n_nagative', np.random.randn(4, 4, 4) + 1j * np.random.randn(4, 4, 4), (-1, -2), (-2, -1), 'backward', ValueError), @@ -485,7 +485,7 @@ class TestHfft2Exception(unittest.TestCase): 4, 4, 4), None, None, 'backward', TypeError), ('test_bool_input', (np.random.randn(4, 4, 4) + 1j * np.random.randn(4, 4, 4)).astype( - np.bool8), None, (-2, -1), 'backward', TypeError), + np.bool_), None, (-2, -1), 'backward', TypeError), ('test_n_nagative', np.random.randn(4, 4, 4) + 1j * np.random.randn(4, 4, 4), (-1, -2), (-2, -1), 'backward', ValueError), @@ -526,7 +526,7 @@ class TestIrfft2Exception(unittest.TestCase): 4, 4, 4), None, None, 'backward', TypeError), ('test_bool_input', (np.random.randn(4, 4, 4) + 1j * np.random.randn(4, 4, 4)).astype( - np.bool8), None, (-2, -1), 'backward', TypeError), + np.bool_), None, (-2, -1), 'backward', TypeError), ('test_n_nagative', np.random.randn(4, 4, 4) + 1j * np.random.randn(4, 4, 4), (-1, -2), (-2, -1), 'backward', ValueError), @@ -568,7 +568,7 @@ class TestHfftnException(unittest.TestCase): 4, 4, 4), None, None, 'backward', TypeError), # ('test_bool_input', # (np.random.randn(4, 4, 4) + 1j * np.random.randn(4, 4, 4) - # ).astype(np.bool8), None, (-2, -1), 'backward', ValueError), + # ).astype(np.bool_), None, (-2, -1), 'backward', ValueError), ('test_n_nagative', np.random.randn(4, 4, 4) + 1j * np.random.randn(4, 4, 4), (-1, -2), (-2, -1), 'backward', ValueError), diff --git a/python/paddle/fluid/tests/unittests/ipu/test_assign_op_ipu.py b/python/paddle/fluid/tests/unittests/ipu/test_assign_op_ipu.py index 3b2034ebe83..af03480fbf6 100644 --- a/python/paddle/fluid/tests/unittests/ipu/test_assign_op_ipu.py +++ b/python/paddle/fluid/tests/unittests/ipu/test_assign_op_ipu.py @@ -86,7 +86,7 @@ class TestAssignBoolValue(TestBase): self.feed_fp32 = {'in_0': data.astype(np.float32)} self.feed_fp16 = {'in_0': data.astype(np.float16)} data = np.random.choice([True, False], size=(2, 3, 1)) - self.assign_bool = data.astype(np.bool) + self.assign_bool = data.astype(np.bool_) @IPUOpTest.static_graph def build_model(self): diff --git a/python/paddle/fluid/tests/unittests/mkldnn/test_mul_int8_mkldnn_op.py b/python/paddle/fluid/tests/unittests/mkldnn/test_mul_int8_mkldnn_op.py index 67d06e7b22c..04d6be13001 100644 --- a/python/paddle/fluid/tests/unittests/mkldnn/test_mul_int8_mkldnn_op.py +++ b/python/paddle/fluid/tests/unittests/mkldnn/test_mul_int8_mkldnn_op.py @@ -64,7 +64,7 @@ class TestMKLDNNMulOpS8S8(OpTest): B_data = np.random.uniform(-127, 127, (5, 20)).astype(np.float32) - quant_B = np.round(B_data * self.scale_y[0]).astype(np.int) + quant_B = np.round(B_data * self.scale_y[0]).astype(np.int_) output = np.dot(A_data, quant_B) scale_output_shift = (self.scale_out) / \ @@ -136,7 +136,7 @@ class TestMKLDNNMulOpS8S8WithFlatten(TestMKLDNNMulOpS8S8): A_data_reshape = A_data.reshape(3 * 4, 4 * 3) B_data_reshape = B_data.reshape(2 * 6, 1 * 2 * 3) - quant_B = np.round(B_data_reshape * self.scale_y[0]).astype(np.int) + quant_B = np.round(B_data_reshape * self.scale_y[0]).astype(np.int_) output = np.dot(A_data_reshape, quant_B) scale_output_shift = (self.scale_out) / \ diff --git a/python/paddle/fluid/tests/unittests/mkldnn/test_softmax_bf16_mkldnn_op.py b/python/paddle/fluid/tests/unittests/mkldnn/test_softmax_bf16_mkldnn_op.py index ca61f961b7a..9986726b3a6 100644 --- a/python/paddle/fluid/tests/unittests/mkldnn/test_softmax_bf16_mkldnn_op.py +++ b/python/paddle/fluid/tests/unittests/mkldnn/test_softmax_bf16_mkldnn_op.py @@ -47,7 +47,7 @@ class TestSoftmaxMKLDNNOp(TestSoftmaxOp): self.shape = self.get_x_shape() self.axis = self.get_axis() - x = np.random.uniform(0.1, 1, self.shape).astype(np.float) + x = np.random.uniform(0.1, 1, self.shape).astype(np.float64) out = convert_float_to_uint16( np.apply_along_axis(stable_softmax, self.axis, x)) diff --git a/python/paddle/fluid/tests/unittests/npu/test_box_coder_op_npu.py b/python/paddle/fluid/tests/unittests/npu/test_box_coder_op_npu.py index 7febcaba45c..d8f442c8441 100644 --- a/python/paddle/fluid/tests/unittests/npu/test_box_coder_op_npu.py +++ b/python/paddle/fluid/tests/unittests/npu/test_box_coder_op_npu.py @@ -193,7 +193,7 @@ class TestBoxCoderOp(OpTest): } if self.use_variance: self.attrs['variance'] = self.prior_box_var.astype( - np.float).flatten() + np.float64).flatten() if self.axis != 0: self.attrs['axis'] = self.axis diff --git a/python/paddle/fluid/tests/unittests/npu/test_density_prior_box_op_npu.py b/python/paddle/fluid/tests/unittests/npu/test_density_prior_box_op_npu.py index 7271644ce82..14aec76af8b 100644 --- a/python/paddle/fluid/tests/unittests/npu/test_density_prior_box_op_npu.py +++ b/python/paddle/fluid/tests/unittests/npu/test_density_prior_box_op_npu.py @@ -84,7 +84,7 @@ class TestNpuDensityPriorBoxOp(OpTest): self.batch_size = 10 self.variances = [0.1, 0.1, 0.2, 0.2] - self.variances = np.array(self.variances, dtype=np.float).flatten() + self.variances = np.array(self.variances, dtype=np.float64).flatten() self.clip = True self.num_priors = 0 diff --git a/python/paddle/fluid/tests/unittests/npu/test_fill_zeros_like_op_npu.py b/python/paddle/fluid/tests/unittests/npu/test_fill_zeros_like_op_npu.py index f9f338a7310..dc7c6f0096b 100644 --- a/python/paddle/fluid/tests/unittests/npu/test_fill_zeros_like_op_npu.py +++ b/python/paddle/fluid/tests/unittests/npu/test_fill_zeros_like_op_npu.py @@ -48,7 +48,7 @@ class TestFillZerosLikeOp(OpTest): class TestFillZerosLikeOpBool(TestFillZerosLikeOp): def init_dtype(self): - self.dtype = np.bool + self.dtype = np.bool_ class TestFillZerosLikeOpFp16(TestFillZerosLikeOp): diff --git a/python/paddle/fluid/tests/unittests/npu/test_prior_box_op_npu.py b/python/paddle/fluid/tests/unittests/npu/test_prior_box_op_npu.py index cfd78c2b05b..5290ad1c0d0 100644 --- a/python/paddle/fluid/tests/unittests/npu/test_prior_box_op_npu.py +++ b/python/paddle/fluid/tests/unittests/npu/test_prior_box_op_npu.py @@ -95,9 +95,9 @@ class TestNPUPriorBox(OpTest): self.set_min_max_aspect_ratios_order() self.real_aspect_ratios = [1, 2.0, 1.0 / 2.0, 3.0, 1.0 / 3.0] self.aspect_ratios = np.array(self.aspect_ratios, - dtype=np.float).flatten() + dtype=np.float64).flatten() self.variances = [0.1, 0.1, 0.2, 0.2] - self.variances = np.array(self.variances, dtype=np.float).flatten() + self.variances = np.array(self.variances, dtype=np.float64).flatten() self.clip = True self.num_priors = len(self.real_aspect_ratios) * len(self.min_sizes) diff --git a/python/paddle/fluid/tests/unittests/npu/test_reduce_max_op_npu.py b/python/paddle/fluid/tests/unittests/npu/test_reduce_max_op_npu.py index 64f66476542..5cedd90d268 100644 --- a/python/paddle/fluid/tests/unittests/npu/test_reduce_max_op_npu.py +++ b/python/paddle/fluid/tests/unittests/npu/test_reduce_max_op_npu.py @@ -106,7 +106,7 @@ class TestReduceMaxOpWithOutDtype_bool(TestNPUReduceMaxOp): } self.outputs = { 'Out': - self.inputs['X'].max(axis=tuple(self.attrs['dim'])).astype(np.bool) + self.inputs['X'].max(axis=tuple(self.attrs['dim'])).astype(np.bool_) } diff --git a/python/paddle/fluid/tests/unittests/npu/test_reduce_min_op_npu.py b/python/paddle/fluid/tests/unittests/npu/test_reduce_min_op_npu.py index 85d1fe94781..10aeea4dee5 100644 --- a/python/paddle/fluid/tests/unittests/npu/test_reduce_min_op_npu.py +++ b/python/paddle/fluid/tests/unittests/npu/test_reduce_min_op_npu.py @@ -106,7 +106,7 @@ class TestReduceMinOpWithOutDtype_bool(TestNPUReduceMinOp): } self.outputs = { 'Out': - self.inputs['X'].min(axis=tuple(self.attrs['dim'])).astype(np.bool) + self.inputs['X'].min(axis=tuple(self.attrs['dim'])).astype(np.bool_) } diff --git a/python/paddle/fluid/tests/unittests/npu/test_reduce_prod_op_npu.py b/python/paddle/fluid/tests/unittests/npu/test_reduce_prod_op_npu.py index c32e105b02a..9e3bc365cee 100644 --- a/python/paddle/fluid/tests/unittests/npu/test_reduce_prod_op_npu.py +++ b/python/paddle/fluid/tests/unittests/npu/test_reduce_prod_op_npu.py @@ -129,7 +129,8 @@ class TestNPUReduceProdWithOutDtype_bool(TestNPUReduceProd): self.attrs = {'dim': [0], 'out_dtype': int(core.VarDesc.VarType.BOOL)} self.outputs = { 'Out': - self.inputs['X'].prod(axis=tuple(self.attrs['dim'])).astype(np.bool) + self.inputs['X'].prod(axis=tuple(self.attrs['dim'])).astype( + np.bool_) } diff --git a/python/paddle/fluid/tests/unittests/npu/test_size_op_npu.py b/python/paddle/fluid/tests/unittests/npu/test_size_op_npu.py index 76fc5846534..e5fd0426742 100755 --- a/python/paddle/fluid/tests/unittests/npu/test_size_op_npu.py +++ b/python/paddle/fluid/tests/unittests/npu/test_size_op_npu.py @@ -72,7 +72,7 @@ class TestSizeOp4(TestSizeOp): def config(self): self.shape = [2**10] - self.dtype = np.bool + self.dtype = np.bool_ class TestSizeOp5(TestSizeOp): diff --git a/python/paddle/fluid/tests/unittests/npu/test_tril_triu_op_npu.py b/python/paddle/fluid/tests/unittests/npu/test_tril_triu_op_npu.py index b3d5fa9a6b5..bdc68d43a22 100644 --- a/python/paddle/fluid/tests/unittests/npu/test_tril_triu_op_npu.py +++ b/python/paddle/fluid/tests/unittests/npu/test_tril_triu_op_npu.py @@ -199,7 +199,7 @@ class TestNPUTrilTriu_bool(TestNPUTrilTriu): self.check_output_with_place(self.place) def init_dtype(self): - self.dtype = np.bool + self.dtype = np.bool_ def initTestCase(self): self.real_op_type = np.random.choice(['triu', 'tril']) diff --git a/python/paddle/fluid/tests/unittests/npu/test_update_loss_scaling_min_op_npu.py b/python/paddle/fluid/tests/unittests/npu/test_update_loss_scaling_min_op_npu.py index 21be9e295d2..48df4ad454a 100644 --- a/python/paddle/fluid/tests/unittests/npu/test_update_loss_scaling_min_op_npu.py +++ b/python/paddle/fluid/tests/unittests/npu/test_update_loss_scaling_min_op_npu.py @@ -37,7 +37,7 @@ class TestUpdateLossScalingOpMinLossScalingBad(TestUpdateLossScalingOpBad): self.init() fluid.core.globals()['FLAGS_min_loss_scaling'] = 1639 - found_inf = np.array([True], dtype=np.bool) + found_inf = np.array([True], dtype=np.bool_) x = np.random.random((1024, 1024)).astype(self.dtype) i = np.random.randint(0, 1024, 1) j = np.random.randint(0, 1024, 1) diff --git a/python/paddle/fluid/tests/unittests/npu/test_update_loss_scaling_op_npu.py b/python/paddle/fluid/tests/unittests/npu/test_update_loss_scaling_op_npu.py index 5299369ff17..678e50247af 100644 --- a/python/paddle/fluid/tests/unittests/npu/test_update_loss_scaling_op_npu.py +++ b/python/paddle/fluid/tests/unittests/npu/test_update_loss_scaling_op_npu.py @@ -34,7 +34,7 @@ class TestUpdateLossScalingOp(OpTest): self.place = paddle.NPUPlace(0) self.init() - found_inf = np.array([False], dtype=np.bool) + found_inf = np.array([False], dtype=np.bool_) x = np.random.random((1024, 1024)).astype(self.dtype) self.inputs = { @@ -82,7 +82,7 @@ class TestUpdateLossScalingOpBad(TestUpdateLossScalingOp): self.place = paddle.NPUPlace(0) self.init() - found_inf = np.array([True], dtype=np.bool) + found_inf = np.array([True], dtype=np.bool_) x = np.random.random((1024, 1024)).astype(self.dtype) i = np.random.randint(0, 1024, 1) j = np.random.randint(0, 1024, 1) diff --git a/python/paddle/fluid/tests/unittests/op_test.py b/python/paddle/fluid/tests/unittests/op_test.py index ded9f188472..ba694f53530 100644 --- a/python/paddle/fluid/tests/unittests/op_test.py +++ b/python/paddle/fluid/tests/unittests/op_test.py @@ -471,7 +471,7 @@ class OpTest(unittest.TestCase): np.dtype(np.int16), np.dtype(np.int8), np.dtype(np.uint8), - np.dtype(np.bool) + np.dtype(np.bool_) ] # check the dtype in dtype_list in order, select the first dtype that in dtype_set for dtype in dtype_list: diff --git a/python/paddle/fluid/tests/unittests/test_assign_op.py b/python/paddle/fluid/tests/unittests/test_assign_op.py index c35d7940a8a..31afb85750e 100644 --- a/python/paddle/fluid/tests/unittests/test_assign_op.py +++ b/python/paddle/fluid/tests/unittests/test_assign_op.py @@ -145,7 +145,7 @@ class TestAssignOApi(unittest.TestCase): def test_assign_NumpyArray(self): with fluid.dygraph.guard(): - array = np.random.random(size=(100, 10)).astype(np.bool) + array = np.random.random(size=(100, 10)).astype(np.bool_) result1 = paddle.zeros(shape=[3, 3], dtype='float32') paddle.assign(array, result1) self.assertTrue(np.allclose(result1.numpy(), array)) diff --git a/python/paddle/fluid/tests/unittests/test_bipartite_match_op.py b/python/paddle/fluid/tests/unittests/test_bipartite_match_op.py index b99892c65e1..87368457632 100644 --- a/python/paddle/fluid/tests/unittests/test_bipartite_match_op.py +++ b/python/paddle/fluid/tests/unittests/test_bipartite_match_op.py @@ -35,7 +35,7 @@ def bipartite_match(distance, match_indices, match_dist): match_sorted = sorted(match_pair, key=lambda tup: tup[2], reverse=True) - row_indices = -1 * np.ones((row, ), dtype=np.int) + row_indices = -1 * np.ones((row, ), dtype=np.int_) idx = 0 for i, j, dist in match_sorted: @@ -69,7 +69,7 @@ def batch_bipartite_match(distance, lod, match_type=None, dist_threshold=None): """ n = len(lod) m = distance.shape[1] - match_indices = -1 * np.ones((n, m), dtype=np.int) + match_indices = -1 * np.ones((n, m), dtype=np.int_) match_dist = np.zeros((n, m), dtype=np.float32) cur_offset = 0 for i in range(n): diff --git a/python/paddle/fluid/tests/unittests/test_box_coder_op.py b/python/paddle/fluid/tests/unittests/test_box_coder_op.py index 63df37f9122..ee064963b2f 100644 --- a/python/paddle/fluid/tests/unittests/test_box_coder_op.py +++ b/python/paddle/fluid/tests/unittests/test_box_coder_op.py @@ -235,7 +235,7 @@ class TestBoxCoderOpWithVariance(OpTest): self.attrs = { 'code_type': 'decode_center_size', 'box_normalized': False, - 'variance': prior_box_var.astype(np.float).flatten(), + 'variance': prior_box_var.astype(np.float64).flatten(), 'axis': axis } self.outputs = {'OutputBox': output_box} diff --git a/python/paddle/fluid/tests/unittests/test_compare_op.py b/python/paddle/fluid/tests/unittests/test_compare_op.py index 06432e4b007..a893b65f5a4 100755 --- a/python/paddle/fluid/tests/unittests/test_compare_op.py +++ b/python/paddle/fluid/tests/unittests/test_compare_op.py @@ -249,8 +249,8 @@ def create_paddle_case(op_type, callback): op = eval("paddle.%s" % (self.op_type)) out = op(x, y) exe = paddle.static.Executor(self.place) - input_x = np.array([True, False, True]).astype(np.bool) - input_y = np.array([True, True, False]).astype(np.bool) + input_x = np.array([True, False, True]).astype(np.bool_) + input_y = np.array([True, True, False]).astype(np.bool_) real_result = callback(input_x, input_y) res, = exe.run(feed={ "x": input_x, @@ -267,8 +267,8 @@ def create_paddle_case(op_type, callback): op = eval("paddle.%s" % (self.op_type)) out = op(x, y) exe = paddle.static.Executor(self.place) - input_x = np.array([True, False, True]).astype(np.bool) - input_y = np.array([True]).astype(np.bool) + input_x = np.array([True, False, True]).astype(np.bool_) + input_y = np.array([True]).astype(np.bool_) real_result = callback(input_x, input_y) res, = exe.run(feed={ "x": input_x, diff --git a/python/paddle/fluid/tests/unittests/test_density_prior_box_op.py b/python/paddle/fluid/tests/unittests/test_density_prior_box_op.py index c00e7588294..4b5d283aa51 100644 --- a/python/paddle/fluid/tests/unittests/test_density_prior_box_op.py +++ b/python/paddle/fluid/tests/unittests/test_density_prior_box_op.py @@ -70,7 +70,7 @@ class TestDensityPriorBoxOp(OpTest): self.batch_size = 10 self.variances = [0.1, 0.1, 0.2, 0.2] - self.variances = np.array(self.variances, dtype=np.float).flatten() + self.variances = np.array(self.variances, dtype=np.float64).flatten() self.clip = True self.num_priors = 0 diff --git a/python/paddle/fluid/tests/unittests/test_fuse_gemm_epilogue_pass.py b/python/paddle/fluid/tests/unittests/test_fuse_gemm_epilogue_pass.py index 29bfca4dd78..2482ab0c549 100644 --- a/python/paddle/fluid/tests/unittests/test_fuse_gemm_epilogue_pass.py +++ b/python/paddle/fluid/tests/unittests/test_fuse_gemm_epilogue_pass.py @@ -27,7 +27,7 @@ def compare(ref, res, atol, rtol): ref = np.array(ref).flatten() res = np.array(res).flatten() - tmp_ref = ref.astype(np.float) + tmp_ref = ref.astype(np.float64) tol = atol + rtol * abs(tmp_ref) diff = abs(res - ref) diff --git a/python/paddle/fluid/tests/unittests/test_fused_multi_transformer_op.py b/python/paddle/fluid/tests/unittests/test_fused_multi_transformer_op.py index ffe6fa8d41a..ecfc8a5bc29 100644 --- a/python/paddle/fluid/tests/unittests/test_fused_multi_transformer_op.py +++ b/python/paddle/fluid/tests/unittests/test_fused_multi_transformer_op.py @@ -164,7 +164,7 @@ class TestFusedMultiTransformerOp(OpTest): self.attn_mask = (self.attn_mask - 1.0) * 1e4 else: self.attn_mask = (np.tril(self.attn_mask) - 1.0) * 1e4 - elif self.attn_mask_type == np.bool: + elif self.attn_mask_type == np.bool_: if self.has_cache_kv and not self.gen_cache_kv: self.attn_mask[:, :, :, -2] = 0 else: @@ -395,7 +395,7 @@ class TestFusedMultiTransformerOp(OpTest): epsilon = 1e-05 ln2_epsilon = 1e-05 - if attn_mask is not None and self.attn_mask_type != np.bool: + if attn_mask is not None and self.attn_mask_type != np.bool_: attn_mask = _convert_attention_mask(attn_mask, x.dtype) qkv_weights, qkv_biases = [], [] diff --git a/python/paddle/fluid/tests/unittests/test_generate_mask_labels_op.py b/python/paddle/fluid/tests/unittests/test_generate_mask_labels_op.py index 8414cd941c2..a86fb0fc459 100644 --- a/python/paddle/fluid/tests/unittests/test_generate_mask_labels_op.py +++ b/python/paddle/fluid/tests/unittests/test_generate_mask_labels_op.py @@ -79,8 +79,8 @@ def poly2mask(xy, k, h, w): u.extend([int(xs + s * t + .5) for t in ts]) k = len(u) - x = np.zeros((k), np.int) - y = np.zeros((k), np.int) + x = np.zeros((k), np.int_) + y = np.zeros((k), np.int_) m = 0 for j in six.moves.xrange(1, k): if u[j] != u[j - 1]: @@ -116,7 +116,7 @@ def poly2mask(xy, k, h, w): b[m - 1] += a[j] j += 1 mask = decode(b, m) - mask = np.array(mask, dtype=np.int).reshape((w, h)) + mask = np.array(mask, dtype=np.int_).reshape((w, h)) mask = mask.transpose((1, 0)) return mask diff --git a/python/paddle/fluid/tests/unittests/test_kron_op.py b/python/paddle/fluid/tests/unittests/test_kron_op.py index 61b5b92c007..51a9cbc63d6 100644 --- a/python/paddle/fluid/tests/unittests/test_kron_op.py +++ b/python/paddle/fluid/tests/unittests/test_kron_op.py @@ -151,7 +151,7 @@ class TestComplexKronOp(OpTest): self.grad_y = self.get_grad_y_by_numpy() def get_grad_x_by_numpy(self): - grad_x = np.zeros(self.x_shape, np.complex) + grad_x = np.zeros(self.x_shape, np.complex128) for x_i in range(self.x_shape[0]): for x_j in range(self.x_shape[1]): for i in range(self.y_shape[0]): @@ -163,7 +163,7 @@ class TestComplexKronOp(OpTest): return grad_x def get_grad_y_by_numpy(self): - grad_y = np.zeros(self.y_shape, np.complex) + grad_y = np.zeros(self.y_shape, np.complex128) for y_i in range(self.y_shape[0]): for y_j in range(self.y_shape[1]): for x_i in range(self.x_shape[0]): diff --git a/python/paddle/fluid/tests/unittests/test_ones_like.py b/python/paddle/fluid/tests/unittests/test_ones_like.py index 0c6e2476be3..31e28fe4787 100644 --- a/python/paddle/fluid/tests/unittests/test_ones_like.py +++ b/python/paddle/fluid/tests/unittests/test_ones_like.py @@ -41,7 +41,7 @@ class TestOnesLikeAPI(unittest.TestCase): # 'bool', 'float32', 'float64', 'int32', 'int64' out1 = ones_like(x) - out2 = ones_like(x, np.bool) + out2 = ones_like(x, np.bool_) out3 = ones_like(x, 'float64') out4 = ones_like(x, 'int32') out5 = ones_like(x, 'int64') @@ -54,7 +54,7 @@ class TestOnesLikeAPI(unittest.TestCase): fetch_list=[out1, out2, out3, out4, out5]) for i, dtype in enumerate( - [np.float32, np.bool, np.float64, np.int32, np.int64]): + [np.float32, np.bool_, np.float64, np.int32, np.int64]): self.assertEqual(outs[i].dtype, dtype) self.assertEqual((outs[i] == np.ones(shape, dtype)).all(), True) @@ -67,7 +67,7 @@ class TestOnesLikeImpeartive(unittest.TestCase): 0) if core.is_compiled_with_cuda() else fluid.CPUPlace() paddle.disable_static(place) x = paddle.to_tensor(np.ones(shape)) - for dtype in [np.bool, np.float32, np.float64, np.int32, np.int64]: + for dtype in [np.bool_, np.float32, np.float64, np.int32, np.int64]: out = ones_like(x, dtype) self.assertEqual((out.numpy() == np.ones(shape, dtype)).all(), True) diff --git a/python/paddle/fluid/tests/unittests/test_prior_box_op.py b/python/paddle/fluid/tests/unittests/test_prior_box_op.py index 2e18f8b748e..b0aaaec246f 100644 --- a/python/paddle/fluid/tests/unittests/test_prior_box_op.py +++ b/python/paddle/fluid/tests/unittests/test_prior_box_op.py @@ -81,9 +81,9 @@ class TestPriorBoxOp(OpTest): self.set_min_max_aspect_ratios_order() self.real_aspect_ratios = [1, 2.0, 1.0 / 2.0, 3.0, 1.0 / 3.0] self.aspect_ratios = np.array(self.aspect_ratios, - dtype=np.float).flatten() + dtype=np.float64).flatten() self.variances = [0.1, 0.1, 0.2, 0.2] - self.variances = np.array(self.variances, dtype=np.float).flatten() + self.variances = np.array(self.variances, dtype=np.float64).flatten() self.clip = True self.num_priors = len(self.real_aspect_ratios) * len(self.min_sizes) diff --git a/python/paddle/fluid/tests/unittests/test_reduce_op.py b/python/paddle/fluid/tests/unittests/test_reduce_op.py index d6fabb44b4f..8d0fcc7ae22 100644 --- a/python/paddle/fluid/tests/unittests/test_reduce_op.py +++ b/python/paddle/fluid/tests/unittests/test_reduce_op.py @@ -965,7 +965,7 @@ class TestAllAPI(unittest.TestCase): paddle.disable_static() for place in self.places: with fluid.dygraph.guard(place): - np_x = np.random.randint(0, 2, (12, 10)).astype(np.bool) + np_x = np.random.randint(0, 2, (12, 10)).astype(np.bool_) x = fluid.layers.assign(np_x) x = fluid.layers.cast(x, 'bool') @@ -1021,7 +1021,7 @@ class TestAnyAPI(unittest.TestCase): paddle.disable_static() for place in self.places: with fluid.dygraph.guard(place): - np_x = np.random.randint(0, 2, (12, 10)).astype(np.bool) + np_x = np.random.randint(0, 2, (12, 10)).astype(np.bool_) x = fluid.layers.assign(np_x) x = fluid.layers.cast(x, 'bool') diff --git a/python/paddle/fluid/tests/unittests/test_signal.py b/python/paddle/fluid/tests/unittests/test_signal.py index 8257630cf20..670b3aa40df 100644 --- a/python/paddle/fluid/tests/unittests/test_signal.py +++ b/python/paddle/fluid/tests/unittests/test_signal.py @@ -81,7 +81,7 @@ def normalize(S, norm=np.inf, axis=0, threshold=None, fill=None): raise Exception("Input must be finite") # All norms only depend on magnitude, let's do that first - mag = np.abs(S).astype(np.float) + mag = np.abs(S).astype(np.float64) # For max/min norms, filling with 1 works fill_norm = 1 @@ -598,8 +598,8 @@ def rand_x(dims=1, np.random.randint(min_dim_len, max_dim_len) for i in range(dims) ] if complex: - return np.random.randn(*shape).astype( - dtype) + 1.j * np.random.randn(*shape).astype(dtype) + return np.random.randn( + *shape).astype(dtype) + 1.j * np.random.randn(*shape).astype(dtype) else: return np.random.randn(*shape).astype(dtype) diff --git a/python/paddle/fluid/tests/unittests/test_update_loss_scaling_op.py b/python/paddle/fluid/tests/unittests/test_update_loss_scaling_op.py index c1294628a4e..0d31dad8199 100644 --- a/python/paddle/fluid/tests/unittests/test_update_loss_scaling_op.py +++ b/python/paddle/fluid/tests/unittests/test_update_loss_scaling_op.py @@ -24,7 +24,7 @@ class TestUpdateLossScalingOp(OpTest): def setUp(self): self.op_type = "update_loss_scaling" self.init() - found_inf = np.array([False], dtype=np.bool) + found_inf = np.array([False], dtype=np.bool_) x = np.random.random((1024, 1024)).astype(self.dtype) self.inputs = { @@ -66,7 +66,7 @@ class TestUpdateLossScalingOpBad(TestUpdateLossScalingOp): def setUp(self): self.op_type = "update_loss_scaling" self.init() - found_inf = np.array([True], dtype=np.bool) + found_inf = np.array([True], dtype=np.bool_) x = np.random.random((1024, 1024)).astype(self.dtype) i = np.random.randint(0, 1024, 1) j = np.random.randint(0, 1024, 1) diff --git a/python/paddle/fluid/tests/unittests/test_zeros_like_op.py b/python/paddle/fluid/tests/unittests/test_zeros_like_op.py index 3be1fb85565..13911dff016 100644 --- a/python/paddle/fluid/tests/unittests/test_zeros_like_op.py +++ b/python/paddle/fluid/tests/unittests/test_zeros_like_op.py @@ -43,7 +43,7 @@ class TestZerosLikeAPI(unittest.TestCase): with program_guard(train_program, startup_program): x = paddle.fluid.data('X', shape) out1 = zeros_like(x) - out2 = zeros_like(x, np.bool) + out2 = zeros_like(x, np.bool_) out3 = zeros_like(x, 'float64') out4 = zeros_like(x, 'int32') out5 = zeros_like(x, 'int64') @@ -54,7 +54,7 @@ class TestZerosLikeAPI(unittest.TestCase): feed={'X': np.ones(shape).astype('float32')}, fetch_list=[out1, out2, out3, out4, out5]) for (i, dtype) in enumerate( - [np.float32, np.bool, np.float64, np.int32, np.int64]): + [np.float32, np.bool_, np.float64, np.int32, np.int64]): self.assertEqual(outs[i].dtype, dtype) self.assertEqual((outs[i] == np.zeros(shape, dtype)).all(), True) @@ -71,7 +71,7 @@ class TestZerosLikeImpeartive(unittest.TestCase): if core.is_compiled_with_cuda() else fluid.CPUPlace()) paddle.disable_static(place) x = paddle.to_tensor(np.ones(shape)) - for dtype in [np.bool, np.float32, np.float64, np.int32, np.int64]: + for dtype in [np.bool_, np.float32, np.float64, np.int32, np.int64]: out = zeros_like(x, dtype) self.assertEqual((out.numpy() == np.zeros(shape, dtype)).all(), True) diff --git a/python/paddle/fluid/tests/unittests/xpu/test_compare_op_xpu.py b/python/paddle/fluid/tests/unittests/xpu/test_compare_op_xpu.py index a4175ec25cf..f33da83bae7 100644 --- a/python/paddle/fluid/tests/unittests/xpu/test_compare_op_xpu.py +++ b/python/paddle/fluid/tests/unittests/xpu/test_compare_op_xpu.py @@ -240,8 +240,8 @@ def create_paddle_case(op_type, callback): op = eval("paddle.%s" % (self.op_type)) out = op(x, y) exe = paddle.static.Executor(self.place) - input_x = np.array([True, False, True]).astype(np.bool) - input_y = np.array([True, True, False]).astype(np.bool) + input_x = np.array([True, False, True]).astype(np.bool_) + input_y = np.array([True, True, False]).astype(np.bool_) real_result = callback(input_x, input_y) res, = exe.run(feed={ "x": input_x, @@ -258,8 +258,8 @@ def create_paddle_case(op_type, callback): op = eval("paddle.%s" % (self.op_type)) out = op(x, y) exe = paddle.static.Executor(self.place) - input_x = np.array([True, False, True]).astype(np.bool) - input_y = np.array([True]).astype(np.bool) + input_x = np.array([True, False, True]).astype(np.bool_) + input_y = np.array([True]).astype(np.bool_) real_result = callback(input_x, input_y) res, = exe.run(feed={ "x": input_x, diff --git a/python/paddle/fluid/tests/unittests/xpu/test_prior_box_op_xpu.py b/python/paddle/fluid/tests/unittests/xpu/test_prior_box_op_xpu.py index c8fcffbd3d3..32dd28f7385 100644 --- a/python/paddle/fluid/tests/unittests/xpu/test_prior_box_op_xpu.py +++ b/python/paddle/fluid/tests/unittests/xpu/test_prior_box_op_xpu.py @@ -98,9 +98,10 @@ class XPUTestPriorBoxOp(XPUOpTestWrapper): self.set_min_max_aspect_ratios_order() self.real_aspect_ratios = [1, 2.0, 1.0 / 2.0, 3.0, 1.0 / 3.0] self.aspect_ratios = np.array(self.aspect_ratios, - dtype=np.float).flatten() + dtype=np.float64).flatten() self.variances = [0.1, 0.1, 0.2, 0.2] - self.variances = np.array(self.variances, dtype=np.float).flatten() + self.variances = np.array(self.variances, + dtype=np.float64).flatten() self.clip = True self.num_priors = len(self.real_aspect_ratios) * len(self.min_sizes) diff --git a/python/paddle/fluid/tests/unittests/xpu/test_update_loss_scaling_op_xpu.py b/python/paddle/fluid/tests/unittests/xpu/test_update_loss_scaling_op_xpu.py index 0aecc48fe35..5ed10d159ae 100644 --- a/python/paddle/fluid/tests/unittests/xpu/test_update_loss_scaling_op_xpu.py +++ b/python/paddle/fluid/tests/unittests/xpu/test_update_loss_scaling_op_xpu.py @@ -31,7 +31,7 @@ class TestUpdateLossScalingOp(XPUOpTest): def setUp(self): self.op_type = "update_loss_scaling" self.init() - found_inf = np.array([False], dtype=np.bool) + found_inf = np.array([False], dtype=np.bool_) x = np.random.random((1024, 1024)).astype(self.dtype) self.inputs = { @@ -75,7 +75,7 @@ class TestUpdateLossScalingOpBad(TestUpdateLossScalingOp): def setUp(self): self.op_type = "update_loss_scaling" self.init() - found_inf = np.array([True], dtype=np.bool) + found_inf = np.array([True], dtype=np.bool_) x = np.random.random((1024, 1024)).astype(self.dtype) i = np.random.randint(0, 1024, 1) j = np.random.randint(0, 1024, 1) diff --git a/python/paddle/nn/layer/conv.py b/python/paddle/nn/layer/conv.py index f724f7cfee5..4ef987eccf2 100644 --- a/python/paddle/nn/layer/conv.py +++ b/python/paddle/nn/layer/conv.py @@ -76,7 +76,7 @@ class _ConvNd(Layer): format(valid_padding_modes, padding_mode)) if padding_mode in {'reflect', 'replicate', 'circular' - } and not isinstance(padding, np.int): + } and not isinstance(padding, int): raise TypeError( "when padding_mode in ['reflect', 'replicate', 'circular'], type of padding must be int" ) diff --git a/python/paddle/tensor/creation.py b/python/paddle/tensor/creation.py index 6b5993744f7..9971a4d5a3e 100644 --- a/python/paddle/tensor/creation.py +++ b/python/paddle/tensor/creation.py @@ -352,7 +352,7 @@ def to_tensor(data, dtype=None, place=None, stop_gradient=True): data = np.array([data]) elif isinstance(data, (list, tuple)): data = np.array(data) - if data.dtype == np.object: + if data.dtype == np.object_: raise ValueError( "\n\tFaild to convert input data to a regular ndarray :\n\t - Usually " "this means the input data contains nested lists with different lengths. " diff --git a/python/paddle/tensor/linalg.py b/python/paddle/tensor/linalg.py index 0089ef21dc9..137c85ac989 100644 --- a/python/paddle/tensor/linalg.py +++ b/python/paddle/tensor/linalg.py @@ -430,7 +430,7 @@ def norm(x, p='fro', axis=None, keepdim=False, name=None): reduce_all = True if axis == None or axis == [] or asvector == True else False axis = axis if axis != None and axis != [] else [0] - reduce_type = 'reduce_max' if porder == np.float( + reduce_type = 'reduce_max' if porder == np.float64( 'inf') else 'reduce_min' helper.append_op(type=reduce_type, inputs={'X': out}, diff --git a/python/paddle/tensor/logic.py b/python/paddle/tensor/logic.py index c4b4c552c67..8834ae1d400 100755 --- a/python/paddle/tensor/logic.py +++ b/python/paddle/tensor/logic.py @@ -146,8 +146,8 @@ def logical_or(x, y, out=None, name=None): import paddle import numpy as np - x_data = np.array([True, False], dtype=np.bool).reshape(2, 1) - y_data = np.array([True, False, True, False], dtype=np.bool).reshape(2, 2) + x_data = np.array([True, False], dtype=np.bool_).reshape(2, 1) + y_data = np.array([True, False, True, False], dtype=np.bool_).reshape(2, 2) x = paddle.to_tensor(x_data) y = paddle.to_tensor(y_data) res = paddle.logical_or(x, y) @@ -191,8 +191,8 @@ def logical_xor(x, y, out=None, name=None): import paddle import numpy as np - x_data = np.array([True, False], dtype=np.bool).reshape([2, 1]) - y_data = np.array([True, False, True, False], dtype=np.bool).reshape([2, 2]) + x_data = np.array([True, False], dtype=np.bool_).reshape([2, 1]) + y_data = np.array([True, False, True, False], dtype=np.bool_).reshape([2, 2]) x = paddle.to_tensor(x_data) y = paddle.to_tensor(y_data) res = paddle.logical_xor(x, y) -- GitLab