From 9894a4fb35fc91646474611864cd933a89fd4a9b Mon Sep 17 00:00:00 2001 From: juncaipeng <52520497+juncaipeng@users.noreply.github.com> Date: Wed, 18 Dec 2019 12:46:39 +0800 Subject: [PATCH] update test precision from fp32 to fp64, test=develop (#21783) --- .../unittests/test_elementwise_min_op.py | 46 +++++++++---------- .../unittests/test_elementwise_pow_op.py | 32 ++++++------- .../fluid/tests/unittests/test_expand_op.py | 6 +-- .../fluid/tests/unittests/test_flatten2_op.py | 2 +- .../fluid/tests/unittests/test_flatten_op.py | 2 +- .../unittests/test_fused_emb_seq_pool_op.py | 2 +- .../tests/unittests/test_gather_nd_op.py | 8 ++-- .../fluid/tests/unittests/test_gather_op.py | 12 ++--- .../tests/unittests/test_grid_sampler_op.py | 14 +++--- .../fluid/tests/unittests/test_gru_op.py | 10 ++-- .../tests/unittests/test_kldiv_loss_op.py | 6 +-- .../tests/unittests/test_lod_reset_op.py | 12 ++--- .../tests/unittests/test_lookup_table_op.py | 4 +- .../unittests/test_lookup_table_v2_op.py | 4 +- 14 files changed, 80 insertions(+), 80 deletions(-) diff --git a/python/paddle/fluid/tests/unittests/test_elementwise_min_op.py b/python/paddle/fluid/tests/unittests/test_elementwise_min_op.py index a25b5994a62..9c6273393a5 100644 --- a/python/paddle/fluid/tests/unittests/test_elementwise_min_op.py +++ b/python/paddle/fluid/tests/unittests/test_elementwise_min_op.py @@ -25,9 +25,9 @@ class TestElementwiseOp(OpTest): # If x and y have the same value, the min() is not differentiable. # So we generate test data by the following method # to avoid them being too close to each other. - x = np.random.uniform(0.1, 1, [13, 17]).astype("float32") - sgn = np.random.choice([-1, 1], [13, 17]).astype("float32") - y = x + sgn * np.random.uniform(0.1, 1, [13, 17]).astype("float32") + x = np.random.uniform(0.1, 1, [13, 17]).astype("float64") + sgn = np.random.choice([-1, 1], [13, 17]).astype("float64") + y = x + sgn * np.random.uniform(0.1, 1, [13, 17]).astype("float64") self.inputs = {'X': x, 'Y': y} self.outputs = {'Out': np.minimum(self.inputs['X'], self.inputs['Y'])} @@ -49,8 +49,8 @@ class TestElementwiseOp(OpTest): class TestElementwiseMinOp_scalar(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_min" - x = np.random.random_integers(-5, 5, [10, 3, 4]).astype("float32") - y = np.array([0.5]).astype("float32") + x = np.random.random_integers(-5, 5, [10, 3, 4]).astype("float64") + y = np.array([0.5]).astype("float64") self.inputs = {'X': x, 'Y': y} self.outputs = {'Out': np.minimum(self.inputs['X'], self.inputs['Y'])} @@ -58,9 +58,9 @@ class TestElementwiseMinOp_scalar(TestElementwiseOp): class TestElementwiseMinOp_Vector(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_min" - x = np.random.random((100, )).astype("float32") - sgn = np.random.choice([-1, 1], (100, )).astype("float32") - y = x + sgn * np.random.uniform(0.1, 1, (100, )).astype("float32") + x = np.random.random((100, )).astype("float64") + sgn = np.random.choice([-1, 1], (100, )).astype("float64") + y = x + sgn * np.random.uniform(0.1, 1, (100, )).astype("float64") self.inputs = {'X': x, 'Y': y} self.outputs = {'Out': np.minimum(self.inputs['X'], self.inputs['Y'])} @@ -68,10 +68,10 @@ class TestElementwiseMinOp_Vector(TestElementwiseOp): class TestElementwiseMinOp_broadcast_0(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_min" - x = np.random.uniform(0.5, 1, (2, 3, 4)).astype(np.float32) - sgn = np.random.choice([-1, 1], (2, )).astype(np.float32) + x = np.random.uniform(0.5, 1, (2, 3, 4)).astype(np.float64) + sgn = np.random.choice([-1, 1], (2, )).astype(np.float64) y = x[:, 0, 0] + sgn * \ - np.random.uniform(1, 2, (2, )).astype(np.float32) + np.random.uniform(1, 2, (2, )).astype(np.float64) self.inputs = {'X': x, 'Y': y} self.attrs = {'axis': 0} @@ -84,10 +84,10 @@ class TestElementwiseMinOp_broadcast_0(TestElementwiseOp): class TestElementwiseMinOp_broadcast_1(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_min" - x = np.random.uniform(0.5, 1, (2, 3, 4)).astype(np.float32) - sgn = np.random.choice([-1, 1], (3, )).astype(np.float32) + x = np.random.uniform(0.5, 1, (2, 3, 4)).astype(np.float64) + sgn = np.random.choice([-1, 1], (3, )).astype(np.float64) y = x[0, :, 0] + sgn * \ - np.random.uniform(1, 2, (3, )).astype(np.float32) + np.random.uniform(1, 2, (3, )).astype(np.float64) self.inputs = {'X': x, 'Y': y} self.attrs = {'axis': 1} @@ -100,10 +100,10 @@ class TestElementwiseMinOp_broadcast_1(TestElementwiseOp): class TestElementwiseMinOp_broadcast_2(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_min" - x = np.random.uniform(0.5, 1, (2, 3, 4)).astype(np.float32) - sgn = np.random.choice([-1, 1], (4, )).astype(np.float32) + x = np.random.uniform(0.5, 1, (2, 3, 4)).astype(np.float64) + sgn = np.random.choice([-1, 1], (4, )).astype(np.float64) y = x[0, 0, :] + sgn * \ - np.random.uniform(1, 2, (4, )).astype(np.float32) + np.random.uniform(1, 2, (4, )).astype(np.float64) self.inputs = {'X': x, 'Y': y} self.outputs = { @@ -115,10 +115,10 @@ class TestElementwiseMinOp_broadcast_2(TestElementwiseOp): class TestElementwiseMinOp_broadcast_3(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_min" - x = np.random.uniform(0.5, 1, (2, 3, 4, 5)).astype(np.float32) - sgn = np.random.choice([-1, 1], (3, 4)).astype(np.float32) + x = np.random.uniform(0.5, 1, (2, 3, 4, 5)).astype(np.float64) + sgn = np.random.choice([-1, 1], (3, 4)).astype(np.float64) y = x[0, :, :, 0] + sgn * \ - np.random.uniform(1, 2, (3, 4)).astype(np.float32) + np.random.uniform(1, 2, (3, 4)).astype(np.float64) self.inputs = {'X': x, 'Y': y} self.attrs = {'axis': 1} @@ -131,10 +131,10 @@ class TestElementwiseMinOp_broadcast_3(TestElementwiseOp): class TestElementwiseMinOp_broadcast_4(TestElementwiseOp): def setUp(self): self.op_type = "elementwise_min" - x = np.random.uniform(0.5, 1, (2, 3, 4, 5)).astype(np.float32) - sgn = np.random.choice([-1, 1], (2, 3, 1, 5)).astype(np.float32) + x = np.random.uniform(0.5, 1, (2, 3, 4, 5)).astype(np.float64) + sgn = np.random.choice([-1, 1], (2, 3, 1, 5)).astype(np.float64) y = x + sgn * \ - np.random.uniform(1, 2, (2, 3, 1, 5)).astype(np.float32) + np.random.uniform(1, 2, (2, 3, 1, 5)).astype(np.float64) self.inputs = {'X': x, 'Y': y} self.outputs = {'Out': np.minimum(self.inputs['X'], self.inputs['Y'])} diff --git a/python/paddle/fluid/tests/unittests/test_elementwise_pow_op.py b/python/paddle/fluid/tests/unittests/test_elementwise_pow_op.py index ffdd6857a9b..81c34073b9f 100644 --- a/python/paddle/fluid/tests/unittests/test_elementwise_pow_op.py +++ b/python/paddle/fluid/tests/unittests/test_elementwise_pow_op.py @@ -23,8 +23,8 @@ class TestElementwisePowOp(OpTest): def setUp(self): self.op_type = "elementwise_pow" self.inputs = { - 'X': np.random.uniform(0.1, 1, [2, 3]).astype("float32"), - 'Y': np.random.uniform(0.1, 1, [2, 3]).astype("float32") + 'X': np.random.uniform(0.1, 1, [2, 3]).astype("float64"), + 'Y': np.random.uniform(0.1, 1, [2, 3]).astype("float64") } self.outputs = {'Out': np.power(self.inputs['X'], self.inputs['Y'])} @@ -39,8 +39,8 @@ class TestElementwisePowOp_scalar(TestElementwisePowOp): def setUp(self): self.op_type = "elementwise_pow" self.inputs = { - 'X': np.random.uniform(0.1, 1, [3, 3, 4]).astype(np.float32), - 'Y': np.random.uniform(0.1, 1, [1]).astype(np.float32) + 'X': np.random.uniform(0.1, 1, [3, 3, 4]).astype(np.float64), + 'Y': np.random.uniform(0.1, 1, [1]).astype(np.float64) } self.outputs = {'Out': np.power(self.inputs['X'], self.inputs['Y'])} @@ -49,8 +49,8 @@ class TestElementwisePowOp_tensor(TestElementwisePowOp): def setUp(self): self.op_type = "elementwise_pow" self.inputs = { - 'X': np.random.uniform(0.1, 1, [32]).astype("float32"), - 'Y': np.random.uniform(0.1, 1, [32]).astype("float32") + 'X': np.random.uniform(0.1, 1, [32]).astype("float64"), + 'Y': np.random.uniform(0.1, 1, [32]).astype("float64") } self.outputs = {'Out': np.power(self.inputs['X'], self.inputs['Y'])} @@ -59,8 +59,8 @@ class TestElementwisePowOp_broadcast_0(TestElementwisePowOp): def setUp(self): self.op_type = "elementwise_pow" self.inputs = { - 'X': np.random.uniform(0.1, 1, [2, 3, 4]).astype("float32"), - 'Y': np.random.uniform(0.1, 1, [4]).astype("float32") + 'X': np.random.uniform(0.1, 1, [2, 3, 4]).astype("float64"), + 'Y': np.random.uniform(0.1, 1, [4]).astype("float64") } self.outputs = {'Out': np.power(self.inputs['X'], self.inputs['Y'])} @@ -69,8 +69,8 @@ class TestElementwisePowOp_broadcast_1(TestElementwisePowOp): def setUp(self): self.op_type = "elementwise_pow" self.inputs = { - 'X': np.random.uniform(0.1, 1, [2, 3, 4]).astype("float32"), - 'Y': np.random.uniform(0.1, 1, [3]).astype("float32") + 'X': np.random.uniform(0.1, 1, [2, 3, 4]).astype("float64"), + 'Y': np.random.uniform(0.1, 1, [3]).astype("float64") } self.attrs = {'axis': 1} self.outputs = { @@ -82,8 +82,8 @@ class TestElementwisePowOp_broadcast_2(TestElementwisePowOp): def setUp(self): self.op_type = "elementwise_pow" self.inputs = { - 'X': np.random.uniform(0.1, 1, [2, 3, 4]).astype("float32"), - 'Y': np.random.uniform(0.1, 1, [2]).astype("float32") + 'X': np.random.uniform(0.1, 1, [2, 3, 4]).astype("float64"), + 'Y': np.random.uniform(0.1, 1, [2]).astype("float64") } self.attrs = {'axis': 0} self.outputs = { @@ -95,8 +95,8 @@ class TestElementwisePowOp_broadcast_3(TestElementwisePowOp): def setUp(self): self.op_type = "elementwise_pow" self.inputs = { - 'X': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype("float32"), - 'Y': np.random.uniform(0.1, 1, [3, 4]).astype("float32") + 'X': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype("float64"), + 'Y': np.random.uniform(0.1, 1, [3, 4]).astype("float64") } self.attrs = {'axis': 1} self.outputs = { @@ -109,8 +109,8 @@ class TestElementwisePowOp_broadcast_4(TestElementwisePowOp): def setUp(self): self.op_type = "elementwise_pow" self.inputs = { - 'X': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype("float32"), - 'Y': np.random.uniform(0.1, 1, [2, 3, 1, 5]).astype("float32") + 'X': np.random.uniform(0.1, 1, [2, 3, 4, 5]).astype("float64"), + 'Y': np.random.uniform(0.1, 1, [2, 3, 1, 5]).astype("float64") } self.outputs = {'Out': np.power(self.inputs['X'], self.inputs['Y'])} diff --git a/python/paddle/fluid/tests/unittests/test_expand_op.py b/python/paddle/fluid/tests/unittests/test_expand_op.py index 0f6f3e31c6b..0509d61efbf 100644 --- a/python/paddle/fluid/tests/unittests/test_expand_op.py +++ b/python/paddle/fluid/tests/unittests/test_expand_op.py @@ -27,7 +27,7 @@ class TestExpandOpRank1(OpTest): self.op_type = "expand" self.init_data() - self.inputs = {'X': np.random.random(self.ori_shape).astype("float32")} + self.inputs = {'X': np.random.random(self.ori_shape).astype("float64")} self.attrs = {'expand_times': self.expand_times} output = np.tile(self.inputs['X'], self.expand_times) self.outputs = {'Out': output} @@ -84,7 +84,7 @@ class TestExpandOpRank1_tensor_attr(OpTest): (1)).astype('int32') * ele)) self.inputs = { - 'X': np.random.random(self.ori_shape).astype("float32"), + 'X': np.random.random(self.ori_shape).astype("float64"), 'expand_times_tensor': expand_times_tensor, } self.attrs = {"expand_times": self.infer_expand_times} @@ -124,7 +124,7 @@ class TestExpandOpRank1_tensor(OpTest): self.init_data() self.inputs = { - 'X': np.random.random(self.ori_shape).astype("float32"), + 'X': np.random.random(self.ori_shape).astype("float64"), 'ExpandTimes': np.array(self.expand_times).astype("int32"), } self.attrs = {} diff --git a/python/paddle/fluid/tests/unittests/test_flatten2_op.py b/python/paddle/fluid/tests/unittests/test_flatten2_op.py index 64aecfea7bf..9fe2d7b20c9 100644 --- a/python/paddle/fluid/tests/unittests/test_flatten2_op.py +++ b/python/paddle/fluid/tests/unittests/test_flatten2_op.py @@ -24,7 +24,7 @@ class TestFlattenOp(OpTest): def setUp(self): self.op_type = "flatten2" self.init_test_case() - self.inputs = {"X": np.random.random(self.in_shape).astype("float32")} + self.inputs = {"X": np.random.random(self.in_shape).astype("float64")} self.init_attrs() self.outputs = { "Out": self.inputs["X"].reshape(self.new_shape), diff --git a/python/paddle/fluid/tests/unittests/test_flatten_op.py b/python/paddle/fluid/tests/unittests/test_flatten_op.py index 502ac1643de..902ce1613a1 100644 --- a/python/paddle/fluid/tests/unittests/test_flatten_op.py +++ b/python/paddle/fluid/tests/unittests/test_flatten_op.py @@ -24,7 +24,7 @@ class TestFlattenOp(OpTest): def setUp(self): self.op_type = "flatten" self.init_test_case() - self.inputs = {"X": np.random.random(self.in_shape).astype("float32")} + self.inputs = {"X": np.random.random(self.in_shape).astype("float64")} self.init_attrs() self.outputs = {"Out": self.inputs["X"].reshape(self.new_shape)} diff --git a/python/paddle/fluid/tests/unittests/test_fused_emb_seq_pool_op.py b/python/paddle/fluid/tests/unittests/test_fused_emb_seq_pool_op.py index 308208be334..0095d438aad 100644 --- a/python/paddle/fluid/tests/unittests/test_fused_emb_seq_pool_op.py +++ b/python/paddle/fluid/tests/unittests/test_fused_emb_seq_pool_op.py @@ -29,7 +29,7 @@ class TestFusedEmbeddingSeqPoolOp(OpTest): def setUp(self): self.op_type = "fused_embedding_seq_pool" self.emb_size = 6 - self.table = np.random.random((17, self.emb_size)).astype("float32") + self.table = np.random.random((17, self.emb_size)).astype("float64") self.ids = np.array([[[4], [3]], [[4], [3]], [[2], [1]], [[16], [1]]]).astype("int64") ids_expand = np.expand_dims(self.ids, axis=1) diff --git a/python/paddle/fluid/tests/unittests/test_gather_nd_op.py b/python/paddle/fluid/tests/unittests/test_gather_nd_op.py index 00418b58a64..95cfdaa5e84 100644 --- a/python/paddle/fluid/tests/unittests/test_gather_nd_op.py +++ b/python/paddle/fluid/tests/unittests/test_gather_nd_op.py @@ -27,7 +27,7 @@ class TestGatherNdOpWithEmptyIndex(OpTest): def setUp(self): self.op_type = "gather_nd" - xnp = np.random.random((5, 20)).astype("float32") + xnp = np.random.random((5, 20)).astype("float64") self.inputs = {'X': xnp, 'Index': np.array([[], []]).astype("int32")} self.outputs = { 'Out': np.vstack((xnp[np.newaxis, :], xnp[np.newaxis, :])) @@ -48,7 +48,7 @@ class TestGatherNdOpWithLowIndex(OpTest): def setUp(self): self.op_type = "gather_nd" xnp = np.array( - [[65, 17, 2], [14, 25, 1], [76, 22, 3]]).astype("float32") + [[65, 17, 2], [14, 25, 1], [76, 22, 3]]).astype("float64") index = np.array([[1], [2]]).astype("int64") self.inputs = {'X': xnp, 'Index': index} @@ -91,7 +91,7 @@ class TestGatherNdOpWithHighRankSame(OpTest): def setUp(self): self.op_type = "gather_nd" shape = (20, 9, 8, 1, 31) - xnp = np.random.rand(*shape) + xnp = np.random.rand(*shape).astype("float64") index = np.vstack([np.random.randint(0, s, size=150) for s in shape]).T self.inputs = {'X': xnp, 'Index': index.astype("int32")} @@ -112,7 +112,7 @@ class TestGatherNdOpWithHighRankDiff(OpTest): def setUp(self): self.op_type = "gather_nd" shape = (20, 9, 8, 1, 31) - xnp = np.random.rand(*shape).astype("double") + xnp = np.random.rand(*shape).astype("float64") index = np.vstack([np.random.randint(0, s, size=1000) for s in shape]).T index_re = index.reshape([10, 5, 20, 5]) diff --git a/python/paddle/fluid/tests/unittests/test_gather_op.py b/python/paddle/fluid/tests/unittests/test_gather_op.py index dffb4b7279b..9f89bd5b5c9 100644 --- a/python/paddle/fluid/tests/unittests/test_gather_op.py +++ b/python/paddle/fluid/tests/unittests/test_gather_op.py @@ -41,7 +41,7 @@ class TestGatherOp(OpTest): For multi-dimension input """ self.x_shape = (10, 20) - self.x_type = "float32" + self.x_type = "float64" self.index = [1, 3, 5] self.index_type = "int32" @@ -52,7 +52,7 @@ class TestCase1(TestGatherOp): For one dimension input """ self.x_shape = (100) - self.x_type = "float32" + self.x_type = "float64" self.index = [1, 3, 5] self.index_type = "int32" @@ -63,7 +63,7 @@ class TestCase2(TestGatherOp): For int64_t index type """ self.x_shape = (10) - self.x_type = "float32" + self.x_type = "float64" self.index = [1, 3, 5] self.index_type = "int64" @@ -74,7 +74,7 @@ class TestCase3(TestGatherOp): For other input type """ self.x_shape = (10, 20) - self.x_type = "double" + self.x_type = "float64" self.index = [1, 3, 5] self.index_type = "int64" @@ -92,7 +92,7 @@ class TestCase5(TestGatherOp): def config(self): self.x_shape = (10, 20) self.attrs = {'overwrite': False} - self.x_type = "float" + self.x_type = "float64" self.index = [1, 1, 3] self.index_type = "int32" @@ -101,7 +101,7 @@ class TestCase6(TestGatherOp): def config(self): self.x_shape = (10, 20) self.attrs = {'overwrite': True} - self.x_type = "float" + self.x_type = "float64" self.index = [1, 3] self.index_type = "int32" diff --git a/python/paddle/fluid/tests/unittests/test_grid_sampler_op.py b/python/paddle/fluid/tests/unittests/test_grid_sampler_op.py index 85c14d4f977..bd5a07769e3 100644 --- a/python/paddle/fluid/tests/unittests/test_grid_sampler_op.py +++ b/python/paddle/fluid/tests/unittests/test_grid_sampler_op.py @@ -34,7 +34,7 @@ def AffineGrid(theta, size): for i in range(len(theta)): ret[i] = np.dot(grid[i].reshape([h * w, 3]), theta[i]) - return ret.reshape([n, h, w, 2]).astype("float32") + return ret.reshape([n, h, w, 2]).astype("float64") def getGridPointValue(data, x, y): @@ -43,7 +43,7 @@ def getGridPointValue(data, x, y): H = data_shape[2] W = data_shape[3] - out = np.zeros(data_shape, dtype='float') + out = np.zeros(data_shape, dtype='float64') for i in range(N): for j in range(H): for k in range(W): @@ -68,8 +68,8 @@ def GridSampler(data, grid): y_max = H - 1 x_max = W - 1 - x = 0.5 * ((x.astype('float32') + 1.0) * x_max) - y = 0.5 * ((y.astype('float32') + 1.0) * y_max) + x = 0.5 * ((x.astype('float64') + 1.0) * x_max) + y = 0.5 * ((y.astype('float64') + 1.0) * y_max) x0 = np.floor(x).astype('int32') x1 = x0 + 1 @@ -86,7 +86,7 @@ def GridSampler(data, grid): vc = getGridPointValue(data, x1, y0) vd = getGridPointValue(data, x1, y1) - out = (wa * va + wb * vb + wc * vc + wd * vd).astype('float32') + out = (wa * va + wb * vb + wc * vc + wd * vd).astype('float64') return out @@ -94,9 +94,9 @@ class TestGridSamplerOp(OpTest): def setUp(self): self.initTestCase() self.op_type = 'grid_sampler' - x = np.random.randint(0, 255, self.x_shape).astype('float32') + x = np.random.randint(0, 255, self.x_shape).astype('float64') - theta = np.zeros(self.theta_shape).astype('float32') + theta = np.zeros(self.theta_shape).astype('float64') for i in range(self.theta_shape[0]): for j in range(2): for k in range(3): diff --git a/python/paddle/fluid/tests/unittests/test_gru_op.py b/python/paddle/fluid/tests/unittests/test_gru_op.py index bce459461a4..cc041991e78 100644 --- a/python/paddle/fluid/tests/unittests/test_gru_op.py +++ b/python/paddle/fluid/tests/unittests/test_gru_op.py @@ -170,20 +170,20 @@ class TestGRUOriginMode(TestGRUOp): class TestGRUOp2(TestGRUOp): def set_confs(self): self.D = 19 - self.dtype = 'float32' + self.dtype = 'float64' class TestGRUOp2Len0(TestGRUOp): def set_confs(self): self.D = 19 self.lod = [[2, 0, 4]] - self.dtype = 'float32' + self.dtype = 'float64' class TestGRUOp2OriginMode(TestGRUOp): def set_confs(self): self.D = 19 - self.dtype = 'float32' + self.dtype = 'float64' self.origin_mode = True @@ -191,7 +191,7 @@ class TestGRUOp2OriginModeLen0(TestGRUOp): def set_confs(self): self.D = 19 self.lod = [[0, 3, 4]] - self.dtype = 'float32' + self.dtype = 'float64' self.origin_mode = True @@ -199,7 +199,7 @@ class TestGRUOp2OriginModeLastLen0(TestGRUOp): def set_confs(self): self.D = 19 self.lod = [[0, 3, 0]] - self.dtype = 'float32' + self.dtype = 'float64' self.origin_mode = True diff --git a/python/paddle/fluid/tests/unittests/test_kldiv_loss_op.py b/python/paddle/fluid/tests/unittests/test_kldiv_loss_op.py index 9aaa3152e56..4402dec3ae5 100644 --- a/python/paddle/fluid/tests/unittests/test_kldiv_loss_op.py +++ b/python/paddle/fluid/tests/unittests/test_kldiv_loss_op.py @@ -36,8 +36,8 @@ class TestKLDivLossOp(OpTest): def setUp(self): self.initTestCase() self.op_type = 'kldiv_loss' - x = np.random.uniform(-10, 10, self.x_shape).astype('float32') - target = np.random.uniform(-10, 10, self.x_shape).astype('float32') + x = np.random.uniform(-10, 10, self.x_shape).astype('float64') + target = np.random.uniform(-10, 10, self.x_shape).astype('float64') self.attrs = {"reduction": self.reduction} @@ -46,7 +46,7 @@ class TestKLDivLossOp(OpTest): 'Target': target, } loss = kldiv_loss(x, target, self.reduction) - self.outputs = {'Loss': loss.astype('float32')} + self.outputs = {'Loss': loss.astype('float64')} def test_check_output(self): self.check_output() diff --git a/python/paddle/fluid/tests/unittests/test_lod_reset_op.py b/python/paddle/fluid/tests/unittests/test_lod_reset_op.py index 391c4d04b2c..4c82605e0c8 100644 --- a/python/paddle/fluid/tests/unittests/test_lod_reset_op.py +++ b/python/paddle/fluid/tests/unittests/test_lod_reset_op.py @@ -22,7 +22,7 @@ from op_test import OpTest class TestLodResetOpByAttr(OpTest): def setUp(self): self.op_type = "lod_reset" - x = np.random.random((10, 20)).astype("float32") + x = np.random.random((10, 20)).astype("float64") lod = [[3, 2, 5]] # target_offset_lod and target_lod are the same lod info represented # in offset-based format and length-based format, respectively. @@ -45,7 +45,7 @@ class TestLodResetOpByAttr(OpTest): class TestLodResetOpByInput(OpTest): def setUp(self): self.op_type = "lod_reset" - x = np.random.random((10, 20)).astype("float32") + x = np.random.random((10, 20)).astype("float64") lod = [[3, 2, 5]] # target_offset_lod and target_lod are the same lod info represented # in offset-based format and length-based format, respectively. @@ -69,7 +69,7 @@ class TestLodResetOpByInput(OpTest): class TestLodResetOpBoth(OpTest): def setUp(self): self.op_type = "lod_reset" - x = np.random.random((10, 20)).astype("float32") + x = np.random.random((10, 20)).astype("float64") lod = [[3, 2, 5]] target_offset_lod_attr = [0, 7, 10] target_offset_lod_in = [0, 4, 7, 10] @@ -93,9 +93,9 @@ class TestLodResetOpBoth(OpTest): class TestLodResetOpYIsLoDTensor(OpTest): def setUp(self): self.op_type = "lod_reset" - x = np.random.random((10, 20)).astype("float32") + x = np.random.random((10, 20)).astype("float64") lod = [[3, 2, 5]] - y = np.random.random((10, 10)).astype("float32") + y = np.random.random((10, 10)).astype("float64") target_lod = [[4, 3, 3]] self.inputs = {'X': (x, lod), 'Y': (y, target_lod)} self.outputs = {'Out': (x, target_lod)} @@ -112,7 +112,7 @@ class TestLodResetOpYIsLoDTensor(OpTest): class TestLodAppendOpByAttr(OpTest): def setUp(self): self.op_type = "lod_reset" - x = np.random.random((10, 20)).astype("float32") + x = np.random.random((10, 20)).astype("float64") lod = [[3, 2, 5]] # target_offset_lod and target_lod are the same lod info represented # in offset-based format and length-based format, respectively. diff --git a/python/paddle/fluid/tests/unittests/test_lookup_table_op.py b/python/paddle/fluid/tests/unittests/test_lookup_table_op.py index 3442cd71d90..0c292170fcb 100644 --- a/python/paddle/fluid/tests/unittests/test_lookup_table_op.py +++ b/python/paddle/fluid/tests/unittests/test_lookup_table_op.py @@ -27,7 +27,7 @@ from paddle.fluid import Program, program_guard class TestLookupTableOp(OpTest): def setUp(self): self.op_type = "lookup_table" - table = np.random.random((17, 31)).astype("float32") + table = np.random.random((17, 31)).astype("float64") ids = np.random.randint(0, 17, 4).astype("int64") ids_expand = np.expand_dims(ids, axis=1) self.inputs = {'W': table, 'Ids': ids_expand} @@ -43,7 +43,7 @@ class TestLookupTableOp(OpTest): class TestLookupTableOpWithTensorIds(OpTest): def setUp(self): self.op_type = "lookup_table" - table = np.random.random((17, 31)).astype("float32") + table = np.random.random((17, 31)).astype("float64") ids = np.random.randint( low=0, high=17, size=(2, 4, 5, 1)).astype("int64") self.inputs = {'W': table, 'Ids': ids} diff --git a/python/paddle/fluid/tests/unittests/test_lookup_table_v2_op.py b/python/paddle/fluid/tests/unittests/test_lookup_table_v2_op.py index 29772cd4004..0fcd6d0afe7 100644 --- a/python/paddle/fluid/tests/unittests/test_lookup_table_v2_op.py +++ b/python/paddle/fluid/tests/unittests/test_lookup_table_v2_op.py @@ -28,7 +28,7 @@ from paddle.fluid import Program, program_guard class TestLookupTableOp(OpTest): def setUp(self): self.op_type = "lookup_table_v2" - table = np.random.random((17, 31)).astype("float32") + table = np.random.random((17, 31)).astype("float64") ids = np.random.randint(0, 17, 4).astype("int64") self.inputs = {'W': table, 'Ids': ids} self.outputs = {'Out': table[ids]} @@ -43,7 +43,7 @@ class TestLookupTableOp(OpTest): class TestLookupTableOpWithTensorIds(OpTest): def setUp(self): self.op_type = "lookup_table_v2" - table = np.random.random((17, 31)).astype("float32") + table = np.random.random((17, 31)).astype("float64") ids = np.random.randint(low=0, high=17, size=(2, 4, 5)).astype("int64") self.inputs = {'W': table, 'Ids': ids} self.outputs = {'Out': table[ids.flatten()].reshape((2, 4, 5, 31))} -- GitLab