未验证 提交 73be70a3 编写于 作者: R ronnywang 提交者: GitHub

[NPU] use np.testing.assert_allclose instead of assertTrue(np.allclose(...)) (#44798)

上级 99fb293c
......@@ -304,8 +304,8 @@ class TestNet(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred, rtol=1e-3))
self.assertTrue(np.allclose(npu_loss, cpu_loss, rtol=1e-3))
np.testing.assert_allclose(npu_pred, cpu_pred, rtol=1e-3)
np.testing.assert_allclose(npu_loss, cpu_loss, rtol=1e-3)
class TestNetWithEpsilonTensor(unittest.TestCase):
......@@ -447,9 +447,9 @@ class TestNetWithEpsilonTensor(unittest.TestCase):
preds.append(pred)
losses.append(loss)
for pred in preds:
self.assertTrue(np.allclose(pred, preds[0]))
np.testing.assert_allclose(pred, preds[0])
for loss in losses:
self.assertTrue(np.allclose(loss, losses[0]))
np.testing.assert_allclose(loss, losses[0])
def test_adam_api(self):
# NOTE(zhiqiu): cpu and gpu has different seed, so should compare separatly.
......
......@@ -249,8 +249,8 @@ class TestNet(unittest.TestCase):
def test_npu(self):
npu_pred, npu_loss = self._test(True)
cpu_pred, cpu_loss = self._test(False)
self.assertTrue(np.allclose(npu_pred, cpu_pred, rtol=1e-3))
self.assertTrue(np.allclose(npu_loss, cpu_loss, rtol=1e-3))
np.testing.assert_allclose(npu_pred, cpu_pred, rtol=5e-3)
np.testing.assert_allclose(npu_loss, cpu_loss, rtol=5e-3)
if __name__ == '__main__':
......
......@@ -95,7 +95,7 @@ class TestCheckFiniteAndUnscale(unittest.TestCase):
out, found_inf = self.run_prog(a, b, scale)
print(out, found_inf)
self.assertTrue(np.allclose(out, (a / b) / scale[0]))
np.testing.assert_allclose(out, (a / b) / scale[0])
self.assertFalse(found_inf[0])
......@@ -159,7 +159,7 @@ class TestCheckFiniteAndUnscaleClearFloatStatus(unittest.TestCase):
out, found_inf = self.run_prog(a, b, scale)
print(out, found_inf)
self.assertTrue(np.allclose(out, (a + b) / scale[0]))
np.testing.assert_allclose(out, (a + b) / scale[0])
self.assertFalse(found_inf[0])
......
......@@ -15,7 +15,7 @@
from __future__ import print_function
import unittest
import numpy
import numpy as np
import sys
sys.path.append("..")
......@@ -27,7 +27,7 @@ import paddle.fluid.framework as framework
import paddle.fluid.layers as layers
paddle.enable_static()
numpy.random.seed(2021)
np.random.seed(2021)
class TestAssignValueNPUOp(op_test.OpTest):
......@@ -50,7 +50,7 @@ class TestAssignValueNPUOp(op_test.OpTest):
self.__class__.use_npu = True
def init_data(self):
self.value = numpy.random.random(size=(2, 5)).astype(numpy.float32)
self.value = np.random.random(size=(2, 5)).astype(np.float32)
self.attrs["fp32_values"] = [float(v) for v in self.value.flat]
def test_forward(self):
......@@ -60,22 +60,22 @@ class TestAssignValueNPUOp(op_test.OpTest):
class TestAssignValueNPUOp2(TestAssignValueNPUOp):
def init_data(self):
self.value = numpy.random.random(size=(2, 5)).astype(numpy.int32)
self.value = np.random.random(size=(2, 5)).astype(np.int32)
self.attrs["int32_values"] = [int(v) for v in self.value.flat]
class TestAssignValueNPUOp3(TestAssignValueNPUOp):
def init_data(self):
self.value = numpy.random.random(size=(2, 5)).astype(numpy.int64)
self.value = np.random.random(size=(2, 5)).astype(np.int64)
self.attrs["int64_values"] = [int(v) for v in self.value.flat]
class TestAssignValueNPUOp4(TestAssignValueNPUOp):
def init_data(self):
self.value = numpy.random.choice(a=[False, True],
size=(2, 5)).astype(numpy.bool)
self.value = np.random.choice(a=[False, True],
size=(2, 5)).astype(np.bool)
self.attrs["bool_values"] = [int(v) for v in self.value.flat]
......@@ -83,7 +83,7 @@ class TestAssignApi(unittest.TestCase):
def setUp(self):
self.init_dtype()
self.value = (-100 + 200 * numpy.random.random(size=(2, 5))).astype(
self.value = (-100 + 200 * np.random.random(size=(2, 5))).astype(
self.dtype)
self.place = fluid.NPUPlace(
0) if fluid.core.is_compiled_with_npu() else fluid.CPUPlace()
......@@ -99,8 +99,10 @@ class TestAssignApi(unittest.TestCase):
exe = fluid.Executor(self.place)
[fetched_x] = exe.run(main_program, feed={}, fetch_list=[x])
self.assertTrue(numpy.array_equal(fetched_x, self.value),
"fetch_x=%s val=%s" % (fetched_x, self.value))
np.testing.assert_allclose(fetched_x,
self.value,
err_msg="fetch_x=%s val=%s" %
(fetched_x, self.value))
self.assertEqual(fetched_x.dtype, self.value.dtype)
......@@ -120,8 +122,8 @@ class TestAssignApi4(TestAssignApi):
def setUp(self):
self.init_dtype()
self.value = numpy.random.choice(a=[False, True],
size=(2, 5)).astype(numpy.bool)
self.value = np.random.choice(a=[False, True],
size=(2, 5)).astype(np.bool)
self.place = fluid.NPUPlace(
0) if fluid.core.is_compiled_with_npu() else fluid.CPUPlace()
......
......@@ -40,7 +40,10 @@ class TestBatchNormOpInference(unittest.TestCase):
self.data_formats = ["NCHW", "NHWC"]
def __assert_close(self, tensor, np_array, msg, atol=1e-4):
self.assertTrue(np.allclose(np.array(tensor), np_array, atol=atol), msg)
np.testing.assert_allclose(np.array(tensor),
np_array,
atol=atol,
err_msg=msg)
def check_with_place(self, place, data_layout, dtype, shape):
epsilon = epsilon = 0.00001
......@@ -475,7 +478,7 @@ class TestDygraphBatchNormTrainableStats(unittest.TestCase):
x = np.random.randn(*shape).astype("float32")
y1 = compute(x, False, False)
y2 = compute(x, True, True)
self.assertTrue(np.allclose(y1, y2))
np.testing.assert_allclose(y1, y2, rtol=1e-5)
def test_static(self):
places = [fluid.NPUPlace(0)]
......@@ -498,7 +501,7 @@ class TestDygraphBatchNormTrainableStats(unittest.TestCase):
x = np.random.randn(*shape).astype("float32")
y1 = compute(x, False, False)
y2 = compute(x, True, True)
self.assertTrue(np.allclose(y1, y2, atol=1e-5))
np.testing.assert_allclose(y1, y2, atol=1e-5)
if __name__ == "__main__":
......
......@@ -60,7 +60,7 @@ def test_static_layer(place,
"weight": weight_np
},
fetch_list=[res])
return static_result
return static_result[0]
def test_static_functional(place,
......@@ -100,7 +100,7 @@ def test_static_functional(place,
"weight": weight_np
},
fetch_list=[res])
return static_result
return static_result[0]
def test_dygraph_layer(place,
......@@ -178,16 +178,18 @@ class TestBCELoss(unittest.TestCase):
dy_result = test_dygraph_layer(place, input_np, label_np,
reduction)
expected = calc_bceloss(input_np, label_np, reduction)
self.assertTrue(np.allclose(static_result, expected))
self.assertTrue(np.allclose(static_result, dy_result))
self.assertTrue(np.allclose(dy_result, expected))
np.testing.assert_allclose(static_result, expected, rtol=1e-6)
np.testing.assert_allclose(static_result, dy_result)
np.testing.assert_allclose(dy_result, expected, rtol=1e-6)
static_functional = test_static_functional(
place, input_np, label_np, reduction)
dy_functional = test_dygraph_functional(place, input_np,
label_np, reduction)
self.assertTrue(np.allclose(static_functional, expected))
self.assertTrue(np.allclose(static_functional, dy_functional))
self.assertTrue(np.allclose(dy_functional, expected))
np.testing.assert_allclose(static_functional,
expected,
rtol=1e-6)
np.testing.assert_allclose(static_functional, dy_functional)
np.testing.assert_allclose(dy_functional, expected, rtol=1e-6)
def test_BCELoss_weight(self):
input_np = np.random.uniform(0.1, 0.8,
......@@ -212,9 +214,9 @@ class TestBCELoss(unittest.TestCase):
label_np,
reduction,
weight_np=weight_np)
self.assertTrue(np.allclose(static_result, expected))
self.assertTrue(np.allclose(static_result, dy_result))
self.assertTrue(np.allclose(dy_result, expected))
np.testing.assert_allclose(static_result, expected, rtol=1e-6)
np.testing.assert_allclose(static_result, dy_result, rtol=1e-6)
np.testing.assert_allclose(dy_result, expected, rtol=1e-6)
static_functional = test_static_functional(place,
input_np,
label_np,
......@@ -225,9 +227,11 @@ class TestBCELoss(unittest.TestCase):
label_np,
reduction,
weight_np=weight_np)
self.assertTrue(np.allclose(static_functional, expected))
self.assertTrue(np.allclose(static_functional, dy_functional))
self.assertTrue(np.allclose(dy_functional, expected))
np.testing.assert_allclose(static_functional, expected, rtol=1e-6)
np.testing.assert_allclose(static_functional,
dy_functional,
rtol=1e-6)
np.testing.assert_allclose(dy_functional, expected, rtol=1e-6)
def test_BCELoss_error(self):
paddle.disable_static(paddle.NPUPlace(0))
......
......@@ -92,9 +92,8 @@ class TestBeamSearchDecodeNPUOp(unittest.TestCase):
expected_data = np.array(
[0, 2, 3, 1, 0, 2, 1, 0, 4, 5, 3, 5, 0, 4, 5, 3, 1], "int64")
self.assertTrue(np.array_equal(np.array(sentence_ids), expected_data))
self.assertTrue(np.array_equal(np.array(sentence_scores),
expected_data))
np.testing.assert_array_equal(np.array(sentence_ids), expected_data)
np.testing.assert_array_equal(np.array(sentence_scores), expected_data)
if __name__ == '__main__':
......
......@@ -173,14 +173,14 @@ class TestClipAPI(unittest.TestCase):
},
fetch_list=[out_1, out_2, out_3, out_4, out_5, out_6, out_7, out_8])
self.assertTrue(np.allclose(res1, data.clip(0.2, 0.8)))
self.assertTrue(np.allclose(res2, data.clip(0.2, 0.9)))
self.assertTrue(np.allclose(res3, data.clip(min=0.3)))
self.assertTrue(np.allclose(res4, data.clip(max=0.7)))
self.assertTrue(np.allclose(res5, data.clip(min=0.2)))
self.assertTrue(np.allclose(res6, data.clip(max=0.8)))
self.assertTrue(np.allclose(res7, data.clip(max=-1)))
self.assertTrue(np.allclose(res8, data))
np.testing.assert_allclose(res1, data.clip(0.2, 0.8))
np.testing.assert_allclose(res2, data.clip(0.2, 0.9))
np.testing.assert_allclose(res3, data.clip(min=0.3))
np.testing.assert_allclose(res4, data.clip(max=0.7))
np.testing.assert_allclose(res5, data.clip(min=0.2))
np.testing.assert_allclose(res6, data.clip(max=0.8))
np.testing.assert_allclose(res7, data.clip(max=-1))
np.testing.assert_allclose(res8, data)
paddle.disable_static()
def test_clip_dygraph(self):
......@@ -200,9 +200,9 @@ class TestClipAPI(unittest.TestCase):
images = paddle.to_tensor(data, dtype='float32')
out_3 = self._executed_api(images, min=v_min, max=v_max)
self.assertTrue(np.allclose(out_1.numpy(), data.clip(0.2, 0.8)))
self.assertTrue(np.allclose(out_2.numpy(), data.clip(0.2, 0.9)))
self.assertTrue(np.allclose(out_3.numpy(), data.clip(0.2, 0.8)))
np.testing.assert_allclose(out_1.numpy(), data.clip(0.2, 0.8))
np.testing.assert_allclose(out_2.numpy(), data.clip(0.2, 0.9))
np.testing.assert_allclose(out_3.numpy(), data.clip(0.2, 0.8))
def test_errors(self):
paddle.enable_static()
......
......@@ -216,5 +216,5 @@ class TestDistBase(unittest.TestCase):
if col_type == "identity":
need_result1 = input1
need_result2 = input2
self.assertTrue(np.allclose(tr0_out, need_result1, rtol=0, atol=0))
self.assertTrue(np.allclose(tr1_out, need_result2, rtol=0, atol=0))
np.testing.assert_allclose(tr0_out, need_result1, rtol=0, atol=0)
np.testing.assert_allclose(tr1_out, need_result2, rtol=0, atol=0)
......@@ -218,10 +218,8 @@ class TestConcatAPIWithLoDTensorArray(unittest.TestCase):
self.assertTrue(self.out_var.shape[self.axis] == -1)
exe = fluid.Executor(self.place)
res = exe.run(self.program, fetch_list=self.out_var)
self.assertTrue(
np.array_equal(
res[0], np.concatenate([self.x] * self.iter_num,
axis=self.axis)))
np.testing.assert_allclose(
res[0], np.concatenate([self.x] * self.iter_num, axis=self.axis))
if __name__ == '__main__':
......
......@@ -142,8 +142,8 @@ class TestCosNet(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred))
self.assertTrue(np.allclose(npu_loss, cpu_loss))
np.testing.assert_allclose(npu_pred, cpu_pred, rtol=1e-6)
np.testing.assert_allclose(npu_loss, cpu_loss, rtol=1e-6)
if __name__ == '__main__':
......
......@@ -33,15 +33,15 @@ class TestCumsumOp(unittest.TestCase):
y = paddle.cumsum(data)
z = np.cumsum(data_np)
self.assertTrue(np.array_equal(z, y.numpy()))
np.testing.assert_array_equal(z, y.numpy())
y = paddle.cumsum(data, axis=0)
z = np.cumsum(data_np, axis=0)
self.assertTrue(np.array_equal(z, y.numpy()))
np.testing.assert_array_equal(z, y.numpy())
y = paddle.cumsum(data, axis=-1)
z = np.cumsum(data_np, axis=-1)
self.assertTrue(np.array_equal(z, y.numpy()))
np.testing.assert_array_equal(z, y.numpy())
y = paddle.cumsum(data, dtype='float32')
self.assertTrue(y.dtype == core.VarDesc.VarType.FP32)
......@@ -51,7 +51,7 @@ class TestCumsumOp(unittest.TestCase):
y = paddle.cumsum(data, axis=-2)
z = np.cumsum(data_np, axis=-2)
self.assertTrue(np.array_equal(z, y.numpy()))
np.testing.assert_array_equal(z, y.numpy())
def run_static(self, use_npu=False):
with fluid.program_guard(fluid.Program()):
......@@ -74,15 +74,15 @@ class TestCumsumOp(unittest.TestCase):
])
z = np.cumsum(data_np)
self.assertTrue(np.allclose(z, out[0]))
np.testing.assert_allclose(z, out[0])
z = np.cumsum(data_np, axis=0)
self.assertTrue(np.allclose(z, out[1]))
np.testing.assert_allclose(z, out[1])
z = np.cumsum(data_np, axis=-1)
self.assertTrue(np.allclose(z, out[2]))
np.testing.assert_allclose(z, out[2])
self.assertTrue(out[3].dtype == np.float32)
self.assertTrue(out[4].dtype == np.int32)
z = np.cumsum(data_np, axis=-2)
self.assertTrue(np.allclose(z, out[5]))
np.testing.assert_allclose(z, out[5])
def test_npu(self):
# Now, npu tests need setting paddle.enable_static()
......
......@@ -269,11 +269,11 @@ class TestDropoutAPI(unittest.TestCase):
fetches = exe.run(fluid.default_main_program(),
feed={"input": in_np},
fetch_list=[res])
self.assertTrue(np.allclose(fetches[0], res_np))
np.testing.assert_allclose(fetches[0], res_np)
fetches2 = exe.run(fluid.default_main_program(),
feed={"input": in_np},
fetch_list=[res6])
self.assertTrue(np.allclose(fetches2[0], res_np2))
np.testing.assert_allclose(fetches2[0], res_np2)
def test_static(self):
for place in self.places:
......
......@@ -178,8 +178,8 @@ class TestElementwiseDivNet(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred))
self.assertTrue(np.allclose(npu_loss, cpu_loss))
np.testing.assert_allclose(npu_pred, cpu_pred, rtol=1e-6)
np.testing.assert_allclose(npu_loss, cpu_loss, rtol=1e-6)
class TestFloatStatus(unittest.TestCase):
......
......@@ -326,8 +326,8 @@ class TestElementwiseMaxNet(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred))
self.assertTrue(np.allclose(npu_loss, cpu_loss))
np.testing.assert_allclose(npu_pred, cpu_pred)
np.testing.assert_allclose(npu_loss, cpu_loss)
if __name__ == '__main__':
......
......@@ -222,8 +222,8 @@ class TestElementwiseMinOpNet(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred))
self.assertTrue(np.allclose(npu_loss, cpu_loss))
np.testing.assert_allclose(npu_pred, cpu_pred, rtol=1e-6)
np.testing.assert_allclose(npu_loss, cpu_loss, rtol=1e-6)
if __name__ == '__main__':
......
......@@ -328,8 +328,8 @@ class TestElementwisePowNet(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred))
self.assertTrue(np.allclose(npu_loss, cpu_loss))
np.testing.assert_allclose(npu_pred, cpu_pred, rtol=1e-6)
np.testing.assert_allclose(npu_loss, cpu_loss, rtol=1e-6)
if __name__ == '__main__':
......
......@@ -231,8 +231,8 @@ class TestSubtractNet(unittest.TestCase):
npu_pred, npu_loss = self._test(True)
cpu_pred, cpu_loos = self._test(False)
self.assertTrue(np.allclose(npu_pred, cpu_pred))
self.assertTrue(np.allclose(npu_loss, cpu_loos))
np.testing.assert_allclose(npu_pred, cpu_pred, rtol=1e-6)
np.testing.assert_allclose(npu_loss, cpu_loos, rtol=1e-6)
if __name__ == '__main__':
......
......@@ -132,7 +132,7 @@ class TestExpandNet(unittest.TestCase):
cpu_loss = self._test(False)
npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_loss, cpu_loss))
np.testing.assert_allclose(npu_loss, cpu_loss, rtol=1e-6)
# ------------------------------------------------
......
......@@ -282,7 +282,7 @@ class TestGatherNdAPI(unittest.TestCase):
output = paddle.fluid.layers.gather(input, index)
output_np = output.numpy()
expected_output = np.array([3, 4])
self.assertTrue(np.allclose(output_np, expected_output))
np.testing.assert_allclose(output_np[0], expected_output)
paddle.enable_static()
......
......@@ -102,7 +102,7 @@ class API_TestGather(unittest.TestCase):
},
fetch_list=[out])
expected_output = np.array([[3, 4], [5, 6]])
self.assertTrue(np.allclose(result, expected_output))
np.testing.assert_allclose(result, expected_output, rtol=1e-5)
def test_out2(self):
with paddle.static.program_guard(paddle.static.Program(),
......@@ -120,7 +120,7 @@ class API_TestGather(unittest.TestCase):
},
fetch_list=[out])
expected_output = gather_numpy(x_np, index_np, axis=0)
self.assertTrue(np.allclose(result, expected_output))
np.testing.assert_allclose(result, expected_output, rtol=1e-5)
class TestGatherGrad(unittest.TestCase):
......@@ -174,8 +174,8 @@ class TestGatherGrad(unittest.TestCase):
npu_pred, npu_loss = self._test(True)
cpu_pred, cpu_loss = self._test(False)
self.assertTrue(np.allclose(npu_pred, cpu_pred))
self.assertTrue(np.allclose(npu_loss, cpu_loss))
np.testing.assert_allclose(npu_pred, cpu_pred, rtol=1e-5)
np.testing.assert_allclose(npu_loss, cpu_loss, rtol=1e-5)
if __name__ == "__main__":
......
......@@ -70,8 +70,12 @@ class TestNPUGaussianRandomOp(OpTest):
hist2, _ = np.histogram(data, range=(-3, 5))
hist2 = hist2.astype("float32")
hist2 /= float(outs[0].size)
self.assertTrue(np.allclose(hist, hist2, rtol=0, atol=0.01),
"hist: " + str(hist) + " hist2: " + str(hist2))
np.testing.assert_allclose(hist,
hist2,
rtol=0,
atol=0.01,
err_msg="hist: " + str(hist) + " hist2: " +
str(hist2))
if __name__ == "__main__":
......
......@@ -150,8 +150,8 @@ class TestGeluNet(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred, atol=1e-3))
self.assertTrue(np.allclose(npu_loss, cpu_loss, atol=1e-3))
np.testing.assert_allclose(npu_pred, cpu_pred, atol=1e-3)
np.testing.assert_allclose(npu_loss, cpu_loss, atol=1e-3)
if __name__ == '__main__':
......
......@@ -113,7 +113,7 @@ class TestHardsigmoidAPI(unittest.TestCase):
res = exe.run(feed={'X': self.x_np}, fetch_list=[out1, out2])
out_ref = ref_hardsigmoid(self.x_np)
for r in res:
self.assertTrue(np.allclose(out_ref, r))
np.testing.assert_allclose(out_ref, r, rtol=1e-6)
def test_dygraph_api(self):
paddle.disable_static(self.place)
......@@ -123,7 +123,7 @@ class TestHardsigmoidAPI(unittest.TestCase):
out2 = m(x)
out_ref = ref_hardsigmoid(self.x_np)
for r in [out1, out2]:
self.assertTrue(np.allclose(out_ref, r.numpy()))
np.testing.assert_allclose(out_ref, r.numpy(), rtol=1e-6)
paddle.enable_static()
def test_fluid_api(self):
......@@ -133,12 +133,12 @@ class TestHardsigmoidAPI(unittest.TestCase):
exe = fluid.Executor(self.place)
res = exe.run(feed={'X': self.x_np}, fetch_list=[out])
out_ref = ref_hardsigmoid(self.x_np, 0.2, 0.5)
self.assertTrue(np.allclose(out_ref, res[0]))
np.testing.assert_allclose(out_ref, res[0])
paddle.disable_static(self.place)
x = paddle.to_tensor(self.x_np)
out = paddle.fluid.layers.hard_sigmoid(x)
self.assertTrue(np.allclose(out_ref, out.numpy()))
np.testing.assert_allclose(out_ref, out.numpy())
paddle.enable_static()
def test_errors(self):
......
......@@ -115,16 +115,20 @@ class TestHardSwishNPUWithCPU(unittest.TestCase):
y = F.hardswish(data)
y.sum().backward()
self.assertTrue(
np.allclose(self.out_y.numpy(), y.numpy()),
"Output of NPU HardSwish forward has diff at " + str(self.place) +
"\nExpect " + str(self.out_y) + "\n" + "But Got" + str(y) +
" in class " + self.__class__.__name__ + ".")
self.assertTrue(
np.allclose(self.out_g.numpy(), data.grad.numpy()),
"Output of NPU HardSwish backward has diff at " + str(self.place) +
"\nExpect " + str(self.out_g) + "\n" + "But Got" + str(data.grad) +
" in class " + self.__class__.__name__ + ".")
np.testing.assert_allclose(
self.out_y.numpy(),
y.numpy(),
err_msg="Output of NPU HardSwish forward has diff at " +
str(self.place) + "\nExpect " + str(self.out_y) + "\n" + "But Got" +
str(y) + " in class " + self.__class__.__name__ + ".",
rtol=1e-5)
np.testing.assert_allclose(
self.out_g.numpy(),
data.grad.numpy(),
err_msg="Output of NPU HardSwish backward has diff at " +
str(self.place) + "\nExpect " + str(self.out_g) + "\n" + "But Got" +
str(data.grad) + " in class " + self.__class__.__name__ + ".",
rtol=1e-5)
if __name__ == '__main__':
......
......@@ -133,7 +133,7 @@ class TestNPUIndexSelectAPI(unittest.TestCase):
return_numpy=False)
expect_out = np.array([[1.0, 2.0, 2.0], [5.0, 6.0, 6.0],
[9.0, 10.0, 10.0]]).astype('float32')
self.assertTrue(np.allclose(expect_out, np.array(res)))
np.testing.assert_allclose(expect_out, np.array(res))
# case 2:
with program_guard(Program(), Program()):
......@@ -149,7 +149,7 @@ class TestNPUIndexSelectAPI(unittest.TestCase):
return_numpy=False)
expect_out = np.array([[1.0, 2.0, 3.0, 4.0], [5.0, 6.0, 7.0, 8.0],
[5.0, 6.0, 7.0, 8.0]]).astype('float32')
self.assertTrue(np.allclose(expect_out, np.array(res)))
np.testing.assert_allclose(expect_out, np.array(res))
def test_dygraph_index_select_api(self):
paddle.set_device("npu:0")
......@@ -163,7 +163,7 @@ class TestNPUIndexSelectAPI(unittest.TestCase):
np_z = z.numpy()
expect_out = np.array([[1.0, 2.0, 3.0, 4.0], [5.0, 6.0, 7.0, 8.0],
[5.0, 6.0, 7.0, 8.0]]).astype('float32')
self.assertTrue(np.allclose(expect_out, np_z))
np.testing.assert_allclose(expect_out, np_z)
# case 2:
x = paddle.to_tensor(self.data_x)
......@@ -172,7 +172,7 @@ class TestNPUIndexSelectAPI(unittest.TestCase):
np_z = z.numpy()
expect_out = np.array([[1.0, 2.0, 2.0], [5.0, 6.0, 6.0],
[9.0, 10.0, 10.0]]).astype('float32')
self.assertTrue(np.allclose(expect_out, np_z))
np.testing.assert_allclose(expect_out, np_z)
if __name__ == '__main__':
......
......@@ -117,7 +117,7 @@ class TestKLDivLossDygraph(unittest.TestCase):
kldiv_criterion = paddle.nn.KLDivLoss(reduction)
pred_loss = kldiv_criterion(paddle.to_tensor(x),
paddle.to_tensor(target))
self.assertTrue(np.allclose(pred_loss.numpy(), gt_loss))
np.testing.assert_allclose(pred_loss.numpy(), gt_loss, rtol=1e-6)
def test_kl_loss_batchmean(self):
self.run_kl_loss('batchmean')
......
......@@ -53,10 +53,11 @@ class TestLayerNormOp(unittest.TestCase):
self.atol = 1e-4
def __assert_close(self, tensor, np_array, msg, atol=1e-4):
self.assertTrue(
np.allclose(np.array(tensor).astype(np_array.dtype),
np.testing.assert_allclose(np.array(tensor).astype(
np_array.dtype).reshape(np_array.shape),
np_array,
atol=atol), msg)
atol=atol,
err_msg=msg)
def check_forward_backward(self,
shape,
......
......@@ -145,8 +145,8 @@ class TestLeakyReluNet(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred))
self.assertTrue(np.allclose(npu_loss, cpu_loss))
np.testing.assert_allclose(npu_pred, cpu_pred, rtol=1e-6)
np.testing.assert_allclose(npu_loss, cpu_loss, rtol=1e-6)
if __name__ == '__main__':
......
......@@ -142,8 +142,8 @@ class TestLogNet(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred, atol=1e-4))
self.assertTrue(np.allclose(npu_loss, cpu_loss, atol=1e-4))
np.testing.assert_allclose(npu_pred, cpu_pred, atol=1e-4)
np.testing.assert_allclose(npu_loss, cpu_loss, atol=1e-4)
if __name__ == '__main__':
......
......@@ -128,13 +128,13 @@ class TestNNLogSoftmaxAPI(unittest.TestCase):
y = logsoftmax(x)
exe = paddle.static.Executor(self.place)
out = exe.run(feed={'x': self.x}, fetch_list=[y])
self.assertTrue(np.allclose(out[0], ref_out))
np.testing.assert_allclose(out[0], ref_out, rtol=1e-6)
# test dygrapg api
paddle.disable_static(self.place)
x = paddle.to_tensor(self.x)
y = logsoftmax(x)
self.assertTrue(np.allclose(y.numpy(), ref_out))
np.testing.assert_allclose(y.numpy(), ref_out, rtol=1e-6)
paddle.enable_static()
def test_check_api(self):
......@@ -161,12 +161,12 @@ class TestNNFunctionalLogSoftmaxAPI(unittest.TestCase):
y = F.log_softmax(x, axis, dtype)
exe = paddle.static.Executor(self.place)
out = exe.run(feed={'x': self.x}, fetch_list=[y])
self.assertTrue(np.allclose(out[0], ref_out))
np.testing.assert_allclose(out[0], ref_out, rtol=1e-6)
paddle.disable_static(self.place)
x = paddle.to_tensor(self.x)
y = F.log_softmax(x, axis, dtype)
self.assertTrue(np.allclose(y.numpy(), ref_out), True)
np.testing.assert_allclose(y.numpy(), ref_out, rtol=1e-6)
paddle.enable_static()
def test_check_api(self):
......
......@@ -76,8 +76,8 @@ class TestMemcpy_FillConstant(unittest.TestCase):
npu_, cpu_ = exe.run(main_program,
feed={},
fetch_list=[npu_var.name, cpu_var.name])
self.assertTrue(np.allclose(npu_, cpu_))
self.assertTrue(np.allclose(cpu_, np.ones((10, 10))))
np.testing.assert_allclose(npu_, cpu_)
np.testing.assert_allclose(cpu_, np.ones((10, 10)))
def test_cpu_cpoy_npu(self):
main_program, npu_var, cpu_var = self.get_prog()
......@@ -90,8 +90,8 @@ class TestMemcpy_FillConstant(unittest.TestCase):
npu_, cpu_ = exe.run(main_program,
feed={},
fetch_list=[npu_var.name, cpu_var.name])
self.assertTrue(np.allclose(npu_, cpu_))
self.assertTrue(np.allclose(npu_, np.zeros((10, 10))))
np.testing.assert_allclose(npu_, cpu_)
np.testing.assert_allclose(npu_, np.zeros((10, 10)))
if __name__ == '__main__':
......
......@@ -316,7 +316,7 @@ class TestMergedMomentum(unittest.TestCase):
outs2 = run_op(False)
self.assertEqual(len(outs1), len(outs2))
for i, (out1, out2) in enumerate(zip(outs1, outs2)):
self.assertTrue(np.allclose(out1, out2, atol=1e-7))
np.testing.assert_allclose(out1, out2, atol=1e-7)
def test_main(self):
self.check_with_place(self.place, multi_precision=False)
......@@ -370,13 +370,13 @@ class TestMergedMomentum2(unittest.TestCase):
outs2 = run_op(use_nesterov=True, use_merged=False)
self.assertEqual(len(outs1), len(outs2))
for i, (out1, out2) in enumerate(zip(outs1, outs2)):
self.assertTrue(np.allclose(out1, out2, atol=1e-7))
np.testing.assert_allclose(out1, out2, atol=1e-7)
outs3 = run_op(use_nesterov=False, use_merged=True)
outs4 = run_op(use_nesterov=False, use_merged=False)
self.assertEqual(len(outs3), len(outs4))
for j, (out3, out4) in enumerate(zip(outs3, outs4)):
self.assertTrue(np.allclose(out3, out4, atol=1e-7))
np.testing.assert_allclose(out3, out4, atol=1e-7)
def test_main(self):
self.check_with_place(self.place, multi_precision=False)
......
......@@ -123,8 +123,8 @@ class TestMeshgridOp3(unittest.TestCase):
},
fetch_list=[grid_x, grid_y])
self.assertTrue(np.allclose(res_1, out_1))
self.assertTrue(np.allclose(res_2, out_2))
np.testing.assert_allclose(res_1, out_1)
np.testing.assert_allclose(res_2, out_2)
class TestMeshgridOp4(unittest.TestCase):
......@@ -154,8 +154,8 @@ class TestMeshgridOp4(unittest.TestCase):
},
fetch_list=[grid_x, grid_y])
self.assertTrue(np.allclose(res_1, out_1))
self.assertTrue(np.allclose(res_2, out_2))
np.testing.assert_allclose(res_1, out_1)
np.testing.assert_allclose(res_2, out_2)
class TestMeshgridOp5(unittest.TestCase):
......@@ -185,8 +185,8 @@ class TestMeshgridOp5(unittest.TestCase):
},
fetch_list=[grid_x, grid_y])
self.assertTrue(np.allclose(res_1, out_1))
self.assertTrue(np.allclose(res_2, out_2))
np.testing.assert_allclose(res_1, out_1)
np.testing.assert_allclose(res_2, out_2)
class TestMeshgridOp6(unittest.TestCase):
......@@ -209,8 +209,8 @@ class TestMeshgridOp6(unittest.TestCase):
tensor_4 = paddle.to_tensor(input_4)
res_3, res_4 = paddle.tensor.meshgrid(tensor_3, tensor_4)
self.assertTrue(np.allclose(res_3.numpy(), out_3))
self.assertTrue(np.allclose(res_4.numpy(), out_4))
np.testing.assert_allclose(res_3.numpy(), out_3)
np.testing.assert_allclose(res_4.numpy(), out_4)
paddle.enable_static()
......@@ -234,8 +234,8 @@ class TestMeshgridOp7(unittest.TestCase):
tensor_4 = paddle.to_tensor(input_4)
res_3, res_4 = paddle.meshgrid([tensor_3, tensor_4])
self.assertTrue(np.allclose(res_3.numpy(), out_3))
self.assertTrue(np.allclose(res_4.numpy(), out_4))
np.testing.assert_allclose(res_3.numpy(), out_3)
np.testing.assert_allclose(res_4.numpy(), out_4)
paddle.enable_static()
......@@ -259,8 +259,8 @@ class TestMeshgridOp8(unittest.TestCase):
tensor_4 = paddle.to_tensor(input_4)
res_3, res_4 = paddle.tensor.meshgrid((tensor_3, tensor_4))
self.assertTrue(np.allclose(res_3.numpy(), out_3))
self.assertTrue(np.allclose(res_4.numpy(), out_4))
np.testing.assert_allclose(res_3.numpy(), out_3)
np.testing.assert_allclose(res_4.numpy(), out_4)
paddle.enable_static()
......
......@@ -285,8 +285,8 @@ class TestMulNet(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred))
self.assertTrue(np.allclose(npu_loss, cpu_loss))
np.testing.assert_allclose(npu_pred, cpu_pred, rtol=1e-6)
np.testing.assert_allclose(npu_loss, cpu_loss, rtol=1e-6)
class TestMulNet3_2(unittest.TestCase):
......@@ -358,9 +358,9 @@ class TestMulNet3_2(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred,
atol=1e-5)) # atol needed on cann 20.3
self.assertTrue(np.allclose(npu_loss, cpu_loss, atol=1e-5))
np.testing.assert_allclose(npu_pred, cpu_pred,
atol=1e-5) # atol needed on cann 20.3
np.testing.assert_allclose(npu_loss, cpu_loss, atol=1e-5)
class TestMulNet3_2_xc2(unittest.TestCase):
......@@ -433,8 +433,8 @@ class TestMulNet3_2_xc2(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred))
self.assertTrue(np.allclose(npu_loss, cpu_loss))
np.testing.assert_allclose(npu_pred, cpu_pred, rtol=1e-6)
np.testing.assert_allclose(npu_loss, cpu_loss, rtol=1e-6)
class TestMulNet4_2(unittest.TestCase):
......@@ -509,9 +509,9 @@ class TestMulNet4_2(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred,
atol=1e-5)) # atol needed on cann 20.3
self.assertTrue(np.allclose(npu_loss, cpu_loss, atol=1e-5))
np.testing.assert_allclose(npu_pred, cpu_pred,
atol=1e-5) # atol needed on cann 20.3
np.testing.assert_allclose(npu_loss, cpu_loss, atol=1e-5)
if __name__ == '__main__':
......
......@@ -77,9 +77,12 @@ class TestMultinomialOp(OpTest):
# normalize the input to get the probability
prob = self.input_np / self.input_np.sum(axis=-1, keepdims=True)
sample_prob = self.sample_output(np.array(outs[0]))
self.assertTrue(
np.allclose(sample_prob, prob, rtol=0, atol=0.01),
"sample_prob: " + str(sample_prob) + "\nprob: " + str(prob))
np.testing.assert_allclose(sample_prob,
prob,
rtol=0,
atol=0.01,
err_msg="sample_prob: " + str(sample_prob) +
"\nprob: " + str(prob))
class TestMultinomialOp2(TestMultinomialOp):
......@@ -122,9 +125,12 @@ class TestMultinomialApi(unittest.TestCase):
sample_prob = sample_output_one_dimension(out.numpy(), 4)
prob = x_numpy / x_numpy.sum(axis=-1, keepdims=True)
self.assertTrue(
np.allclose(sample_prob, prob, rtol=0, atol=0.01),
"sample_prob: " + str(sample_prob) + "\nprob: " + str(prob))
np.testing.assert_allclose(sample_prob,
prob,
rtol=0,
atol=0.01,
err_msg="sample_prob: " + str(sample_prob) +
"\nprob: " + str(prob))
paddle.enable_static()
def test_dygraph2(self):
......@@ -137,9 +143,12 @@ class TestMultinomialApi(unittest.TestCase):
sample_prob = sample_output_two_dimension(out.numpy(), [3, 4])
prob = x_numpy / x_numpy.sum(axis=-1, keepdims=True)
self.assertTrue(
np.allclose(sample_prob, prob, rtol=0, atol=0.01),
"sample_prob: " + str(sample_prob) + "\nprob: " + str(prob))
np.testing.assert_allclose(sample_prob,
prob,
rtol=0,
atol=0.01,
err_msg="sample_prob: " + str(sample_prob) +
"\nprob: " + str(prob))
paddle.enable_static()
def test_dygraph3(self):
......@@ -182,9 +191,12 @@ class TestMultinomialApi(unittest.TestCase):
sample_prob = sample_output_one_dimension(out, 4)
prob = x_np / x_np.sum(axis=-1, keepdims=True)
self.assertTrue(
np.allclose(sample_prob, prob, rtol=0, atol=0.01),
"sample_prob: " + str(sample_prob) + "\nprob: " + str(prob))
np.testing.assert_allclose(sample_prob,
prob,
rtol=0,
atol=0.01,
err_msg="sample_prob: " + str(sample_prob) +
"\nprob: " + str(prob))
class TestMultinomialAlias(unittest.TestCase):
......
......@@ -466,10 +466,10 @@ class TestNearestAPI(unittest.TestCase):
out_h=12,
out_w=12,
align_corners=False)
self.assertTrue(
np.allclose(results[0], np.transpose(expect_res, (0, 2, 3, 1))))
np.testing.assert_allclose(results[0],
np.transpose(expect_res, (0, 2, 3, 1)))
for i in range(len(results) - 1):
self.assertTrue(np.allclose(results[i + 1], expect_res))
np.testing.assert_allclose(results[i + 1], expect_res)
class TestNearestInterpException(unittest.TestCase):
......
......@@ -398,7 +398,7 @@ class TestNearestInterpOpAPI_dy(unittest.TestCase):
scale_factor=scale,
mode="nearest",
align_corners=False)
self.assertTrue(np.allclose(out.numpy(), expect_res))
np.testing.assert_allclose(out.numpy(), expect_res)
if __name__ == "__main__":
......
......@@ -202,8 +202,8 @@ class TestPadAPI(unittest.TestCase):
mode,
value,
data_format="NDHWC")
self.assertTrue(np.allclose(fetches[0], np_out1))
self.assertTrue(np.allclose(fetches[1], np_out2))
np.testing.assert_allclose(fetches[0], np_out1)
np.testing.assert_allclose(fetches[1], np_out2)
def test_dygraph_1(self):
paddle.disable_static()
......@@ -238,8 +238,8 @@ class TestPadAPI(unittest.TestCase):
value=value,
data_format="NDHWC")
self.assertTrue(np.allclose(y1.numpy(), np_out1))
self.assertTrue(np.allclose(y2.numpy(), np_out2))
np.testing.assert_allclose(y1.numpy(), np_out1)
np.testing.assert_allclose(y2.numpy(), np_out2)
def test_dygraph_2(self):
paddle.disable_static()
......@@ -274,8 +274,8 @@ class TestPadAPI(unittest.TestCase):
value=value,
data_format="NHWC")
self.assertTrue(np.allclose(y1.numpy(), np_out1))
self.assertTrue(np.allclose(y2.numpy(), np_out2))
np.testing.assert_allclose(y1.numpy(), np_out1)
np.testing.assert_allclose(y2.numpy(), np_out2)
def test_dygraph_3(self):
paddle.disable_static()
......@@ -310,8 +310,8 @@ class TestPadAPI(unittest.TestCase):
value=value,
data_format="NLC")
self.assertTrue(np.allclose(y1.numpy(), np_out1))
self.assertTrue(np.allclose(y2.numpy(), np_out2))
np.testing.assert_allclose(y1.numpy(), np_out1)
np.testing.assert_allclose(y2.numpy(), np_out2)
class TestPad1dAPI(unittest.TestCase):
......@@ -360,14 +360,14 @@ class TestPad1dAPI(unittest.TestCase):
"constant",
value=value,
data_format="NCL")
self.assertTrue(np.allclose(output.numpy(), np_out))
np.testing.assert_allclose(output.numpy(), np_out)
output = pad_constant_int(data)
np_out = self._get_numpy_out(input_data, [pad_int] * 2,
"constant",
value=value,
data_format="NCL")
self.assertTrue(np.allclose(output.numpy(), np_out))
np.testing.assert_allclose(output.numpy(), np_out)
class TestPad2dAPI(unittest.TestCase):
......@@ -418,14 +418,14 @@ class TestPad2dAPI(unittest.TestCase):
"constant",
value=value,
data_format="NCHW")
self.assertTrue(np.allclose(output.numpy(), np_out))
np.testing.assert_allclose(output.numpy(), np_out)
output = pad_constant_int(data)
np_out = self._get_numpy_out(input_data, [pad_int] * 4,
"constant",
value=value,
data_format="NCHW")
self.assertTrue(np.allclose(output.numpy(), np_out))
np.testing.assert_allclose(output.numpy(), np_out)
class TestPad3dAPI(unittest.TestCase):
......@@ -478,14 +478,14 @@ class TestPad3dAPI(unittest.TestCase):
"constant",
value=value,
data_format="NCDHW")
self.assertTrue(np.allclose(output.numpy(), np_out))
np.testing.assert_allclose(output.numpy(), np_out)
output = pad_constant_int(data)
np_out = self._get_numpy_out(input_data, [pad_int] * 6,
"constant",
value=value,
data_format="NCDHW")
self.assertTrue(np.allclose(output.numpy(), np_out))
np.testing.assert_allclose(output.numpy(), np_out)
class TestPad3dOpNpuError(unittest.TestCase):
......
......@@ -142,8 +142,8 @@ class TestPowNet(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred))
self.assertTrue(np.allclose(npu_loss, cpu_loss))
np.testing.assert_allclose(npu_pred, cpu_pred, rtol=1e-6)
np.testing.assert_allclose(npu_loss, cpu_loss, rtol=1e-6)
if __name__ == '__main__':
......
......@@ -150,8 +150,8 @@ class TestReduceSumNet(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred))
self.assertTrue(np.allclose(npu_loss, cpu_loss))
np.testing.assert_allclose(npu_pred, cpu_pred)
np.testing.assert_allclose(npu_loss, cpu_loss)
class TestReduceSumNet2(TestReduceSumNet):
......
......@@ -163,8 +163,8 @@ class TestRelu6Net(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred))
self.assertTrue(np.allclose(npu_loss, cpu_loss))
np.testing.assert_allclose(npu_pred, cpu_pred, rtol=1e-6)
np.testing.assert_allclose(npu_loss, cpu_loss, rtol=1e-6)
if __name__ == '__main__':
......
......@@ -157,8 +157,8 @@ class TestReluNet(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred))
self.assertTrue(np.allclose(npu_loss, cpu_loss))
np.testing.assert_allclose(npu_pred, cpu_pred, rtol=1e-6)
np.testing.assert_allclose(npu_loss, cpu_loss, rtol=1e-6)
if __name__ == '__main__':
......
......@@ -88,8 +88,8 @@ class TestNet(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred, rtol=1e-3))
self.assertTrue(np.allclose(npu_loss, cpu_loss, rtol=1e-3))
np.testing.assert_allclose(npu_pred, cpu_pred, rtol=1e-3)
np.testing.assert_allclose(npu_loss, cpu_loss, rtol=1e-3)
class TestCenteredNet(unittest.TestCase):
......@@ -151,8 +151,8 @@ class TestCenteredNet(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred, rtol=1e-3))
self.assertTrue(np.allclose(npu_loss, cpu_loss, rtol=1e-3))
np.testing.assert_allclose(npu_pred, cpu_pred, rtol=1e-3)
np.testing.assert_allclose(npu_loss, cpu_loss, rtol=1e-3)
if __name__ == "__main__":
......
......@@ -112,8 +112,8 @@ class TestNet(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred))
self.assertTrue(np.allclose(npu_loss, cpu_loss))
np.testing.assert_allclose(npu_pred, cpu_pred, rtol=1e-6)
np.testing.assert_allclose(npu_loss, cpu_loss, rtol=1e-6)
if __name__ == '__main__':
......
......@@ -316,8 +316,8 @@ class TestSliceNet(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred))
self.assertTrue(np.allclose(npu_loss, cpu_loss))
np.testing.assert_allclose(npu_pred, cpu_pred, rtol=1e-6)
np.testing.assert_allclose(npu_loss, cpu_loss, rtol=1e-6)
class TestSliceOpDecsDim(OpTest):
......
......@@ -118,8 +118,8 @@ class TestSoftmaxNet(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred, rtol=1e-2))
self.assertTrue(np.allclose(npu_loss, cpu_loss, rtol=1e-2))
np.testing.assert_allclose(npu_pred, cpu_pred, rtol=1e-2)
np.testing.assert_allclose(npu_loss, cpu_loss, rtol=1e-2)
if __name__ == '__main__':
......
......@@ -155,8 +155,8 @@ class TestPowNet(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred))
self.assertTrue(np.allclose(npu_loss, cpu_loss))
np.testing.assert_allclose(npu_pred, cpu_pred, rtol=1e-5)
np.testing.assert_allclose(npu_loss, cpu_loss, rtol=1e-5)
if __name__ == '__main__':
......
......@@ -113,8 +113,8 @@ class API_TestSplit(unittest.TestCase):
input1 = np.random.random([1, 10]).astype('float32')
r0, r1 = exe.run(feed={"data": input1}, fetch_list=[x0, x1])
ex_x0, ex_x1 = np.split(input1, (3, ), axis=1)
self.assertTrue(np.allclose(ex_x0, r0))
self.assertTrue(np.allclose(ex_x1, r1))
np.testing.assert_allclose(ex_x0, r0)
np.testing.assert_allclose(ex_x1, r1)
class API_TestSplit2(unittest.TestCase):
......@@ -128,8 +128,8 @@ class API_TestSplit2(unittest.TestCase):
input1 = np.random.random([1, 10]).astype('float32')
r0, r1 = exe.run(feed={"data": input1}, fetch_list=[x0, x1])
ex_x0, ex_x1 = np.split(input1, 2, axis=1)
self.assertTrue(np.allclose(ex_x0, r0))
self.assertTrue(np.allclose(ex_x1, r1))
np.testing.assert_allclose(ex_x0, r0)
np.testing.assert_allclose(ex_x1, r1)
class API_TestDygraphSplit(unittest.TestCase):
......@@ -144,9 +144,9 @@ class API_TestDygraphSplit(unittest.TestCase):
x1_out = x1.numpy()
x2_out = x2.numpy()
ex_x0, ex_x1, ex_x2 = np.split(input_1, 3, axis=1)
self.assertTrue(np.allclose(ex_x0, x0_out))
self.assertTrue(np.allclose(ex_x1, x1_out))
self.assertTrue(np.allclose(ex_x2, x2_out))
np.testing.assert_allclose(ex_x0, x0_out)
np.testing.assert_allclose(ex_x1, x1_out)
np.testing.assert_allclose(ex_x2, x2_out)
def test_out2(self):
with fluid.dygraph.guard(paddle.NPUPlace(0)):
......@@ -158,9 +158,9 @@ class API_TestDygraphSplit(unittest.TestCase):
x1_out = x1.numpy()
x2_out = x2.numpy()
ex_x0, ex_x1, ex_x2 = np.split(input_1, (1, 3), axis=1)
self.assertTrue(np.allclose(ex_x0, x0_out))
self.assertTrue(np.allclose(ex_x1, x1_out))
self.assertTrue(np.allclose(ex_x2, x2_out))
np.testing.assert_allclose(ex_x0, x0_out)
np.testing.assert_allclose(ex_x1, x1_out)
np.testing.assert_allclose(ex_x2, x2_out)
if __name__ == '__main__':
......
......@@ -145,8 +145,8 @@ class TestSqrtNet(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred))
self.assertTrue(np.allclose(npu_loss, cpu_loss))
np.testing.assert_allclose(npu_pred, cpu_pred, rtol=1e-6)
np.testing.assert_allclose(npu_loss, cpu_loss, rtol=1e-6)
if __name__ == '__main__':
......
......@@ -142,8 +142,8 @@ class TestSquareNet(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred))
self.assertTrue(np.allclose(npu_loss, cpu_loss))
np.testing.assert_allclose(npu_pred, cpu_pred, rtol=1e-6)
np.testing.assert_allclose(npu_loss, cpu_loss, rtol=1e-6)
if __name__ == '__main__':
......
......@@ -143,7 +143,7 @@ class API_TestSqueeze(unittest.TestCase):
result, = exe.run(feed={"data1": input1},
fetch_list=[result_squeeze])
expected_result = np.squeeze(input1, axis=1)
self.assertTrue(np.allclose(expected_result, result))
np.testing.assert_allclose(expected_result, result)
class API_TestStaticSqueeze_(API_TestSqueeze):
......@@ -168,7 +168,7 @@ class API_TestDygraphSqueeze(unittest.TestCase):
output = self.squeeze(input, axis=[1])
out_np = output.numpy()
expected_out = np.squeeze(input_1, axis=1)
self.assertTrue(np.allclose(expected_out, out_np))
np.testing.assert_allclose(expected_out, out_np)
def test_out_int8(self):
paddle.disable_static()
......@@ -178,7 +178,7 @@ class API_TestDygraphSqueeze(unittest.TestCase):
output = self.squeeze(input, axis=[1])
out_np = output.numpy()
expected_out = np.squeeze(input_1, axis=1)
self.assertTrue(np.allclose(expected_out, out_np))
np.testing.assert_allclose(expected_out, out_np)
def test_out_uint8(self):
paddle.disable_static()
......@@ -188,7 +188,7 @@ class API_TestDygraphSqueeze(unittest.TestCase):
output = self.squeeze(input, axis=[1])
out_np = output.numpy()
expected_out = np.squeeze(input_1, axis=1)
self.assertTrue(np.allclose(expected_out, out_np))
np.testing.assert_allclose(expected_out, out_np)
def test_axis_not_list(self):
paddle.disable_static()
......@@ -198,7 +198,7 @@ class API_TestDygraphSqueeze(unittest.TestCase):
output = self.squeeze(input, axis=1)
out_np = output.numpy()
expected_out = np.squeeze(input_1, axis=1)
self.assertTrue(np.allclose(expected_out, out_np))
np.testing.assert_allclose(expected_out, out_np)
def test_dimension_not_1(self):
paddle.disable_static()
......@@ -208,7 +208,7 @@ class API_TestDygraphSqueeze(unittest.TestCase):
output = self.squeeze(input, axis=(1, 0))
out_np = output.numpy()
expected_out = np.squeeze(input_1, axis=1)
self.assertTrue(np.allclose(expected_out, out_np))
np.testing.assert_allclose(expected_out, out_np)
class API_TestDygraphSqueezeInplace(API_TestDygraphSqueeze):
......
......@@ -157,9 +157,8 @@ class TestStackAPIWithLoDTensorArray(unittest.TestCase):
self.assertTrue(self.out_var.shape[self.axis] == -1)
exe = fluid.Executor(self.place)
res = exe.run(self.program, fetch_list=self.out_var)
self.assertTrue(
np.array_equal(res[0],
np.stack([self.x] * self.iter_num, axis=self.axis)))
np.testing.assert_allclose(
res[0], np.stack([self.x] * self.iter_num, axis=self.axis))
class TestTensorStackAPIWithLoDTensorArray(unittest.TestCase):
......@@ -192,9 +191,8 @@ class TestTensorStackAPIWithLoDTensorArray(unittest.TestCase):
self.assertTrue(self.out_var.shape[self.axis] == -1)
exe = fluid.Executor(self.place)
res = exe.run(self.program, fetch_list=self.out_var)
self.assertTrue(
np.array_equal(res[0],
np.stack([self.x] * self.iter_num, axis=self.axis)))
np.testing.assert_allclose(
res[0], np.stack([self.x] * self.iter_num, axis=self.axis))
class API_test(unittest.TestCase):
......@@ -217,7 +215,7 @@ class API_test(unittest.TestCase):
},
fetch_list=[result_stack])
expected_result = np.stack([input1, input2, input3], axis=0)
self.assertTrue(np.allclose(expected_result, result))
np.testing.assert_allclose(expected_result, result)
def test_single_tensor_error(self):
with fluid.program_guard(fluid.Program(), fluid.Program()):
......@@ -238,14 +236,14 @@ class API_DygraphTest(unittest.TestCase):
result = paddle.stack([x1, x2, x3])
result_np = result.numpy()
expected_result = np.stack([data1, data2, data3])
self.assertTrue(np.allclose(expected_result, result_np))
np.testing.assert_allclose(expected_result, result_np)
with fluid.dygraph.guard(place=paddle.NPUPlace(0)):
y1 = fluid.dygraph.to_variable(data1)
result = paddle.stack([y1], axis=0)
result_np_2 = result.numpy()
expected_result_2 = np.stack([data1], axis=0)
self.assertTrue(np.allclose(expected_result_2, result_np_2))
np.testing.assert_allclose(expected_result_2, result_np_2)
def test_single_tensor_error(self):
with fluid.dygraph.guard(place=paddle.NPUPlace(0)):
......
......@@ -145,8 +145,8 @@ class TestTanhNet(unittest.TestCase):
cpu_pred, cpu_loss = self._test(False)
npu_pred, npu_loss = self._test(True)
self.assertTrue(np.allclose(npu_pred, cpu_pred))
self.assertTrue(np.allclose(npu_loss, cpu_loss))
np.testing.assert_allclose(npu_pred, cpu_pred, rtol=1e-6)
np.testing.assert_allclose(npu_loss, cpu_loss, rtol=1e-6)
if __name__ == '__main__':
......
......@@ -241,47 +241,47 @@ class TestTopKAPI(unittest.TestCase):
# test case for basic test case 1
paddle_result = paddle.topk(input_tensor, k=2)
numpy_result = numpy_topk(self.input_data, k=2)
self.assertTrue(np.allclose(paddle_result[0].numpy(), numpy_result[0]))
self.assertTrue(np.allclose(paddle_result[1].numpy(), numpy_result[1]))
np.testing.assert_allclose(paddle_result[0].numpy(), numpy_result[0])
np.testing.assert_allclose(paddle_result[1].numpy(), numpy_result[1])
# test case for basic test case 2 with axis
paddle_result = paddle.topk(input_tensor, k=2, axis=1)
numpy_result = numpy_topk(self.input_data, k=2, axis=1)
self.assertTrue(np.allclose(paddle_result[0].numpy(), numpy_result[0]))
self.assertTrue(np.allclose(paddle_result[1].numpy(), numpy_result[1]))
np.testing.assert_allclose(paddle_result[0].numpy(), numpy_result[0])
np.testing.assert_allclose(paddle_result[1].numpy(), numpy_result[1])
# test case for basic test case 3 with tensor K
k_tensor = paddle.to_tensor(np.array([2]))
paddle_result = paddle.topk(input_tensor, k=k_tensor, axis=1)
numpy_result = numpy_topk(self.input_data, k=2, axis=1)
self.assertTrue(np.allclose(paddle_result[0].numpy(), numpy_result[0]))
self.assertTrue(np.allclose(paddle_result[1].numpy(), numpy_result[1]))
np.testing.assert_allclose(paddle_result[0].numpy(), numpy_result[0])
np.testing.assert_allclose(paddle_result[1].numpy(), numpy_result[1])
# test case for basic test case 4 with tensor largest
k_tensor = paddle.to_tensor(np.array([2]))
paddle_result = paddle.topk(input_tensor, k=2, axis=1, largest=False)
numpy_result = numpy_topk(self.input_data, k=2, axis=1, largest=False)
self.assertTrue(np.allclose(paddle_result[0].numpy(), numpy_result[0]))
self.assertTrue(np.allclose(paddle_result[1].numpy(), numpy_result[1]))
np.testing.assert_allclose(paddle_result[0].numpy(), numpy_result[0])
np.testing.assert_allclose(paddle_result[1].numpy(), numpy_result[1])
# test case for basic test case 5 with axis -1
k_tensor = paddle.to_tensor(np.array([2]))
paddle_result = paddle.topk(input_tensor, k=2, axis=-1, largest=False)
numpy_result = numpy_topk(self.input_data, k=2, axis=-1, largest=False)
self.assertTrue(np.allclose(paddle_result[0].numpy(), numpy_result[0]))
self.assertTrue(np.allclose(paddle_result[1].numpy(), numpy_result[1]))
np.testing.assert_allclose(paddle_result[0].numpy(), numpy_result[0])
np.testing.assert_allclose(paddle_result[1].numpy(), numpy_result[1])
# test case for basic test case 6 for the partial sort
paddle_result = paddle.topk(large_input_tensor, k=1, axis=-1)
numpy_result = numpy_topk(self.large_input_data, k=1, axis=-1)
self.assertTrue(np.allclose(paddle_result[0].numpy(), numpy_result[0]))
self.assertTrue(np.allclose(paddle_result[1].numpy(), numpy_result[1]))
np.testing.assert_allclose(paddle_result[0].numpy(), numpy_result[0])
np.testing.assert_allclose(paddle_result[1].numpy(), numpy_result[1])
# test case for basic test case 7 for the unsorted
paddle_result = paddle.topk(input_tensor, k=2, axis=1, sorted=False)
sort_paddle = numpy_topk(np.array(paddle_result[0].numpy()),
axis=1,
k=2)
numpy_result = numpy_topk(self.input_data, k=2, axis=1)
self.assertTrue(np.allclose(sort_paddle[0], numpy_result[0]))
np.testing.assert_allclose(sort_paddle[0], numpy_result[0])
def run_static(self, place):
paddle.enable_static()
......@@ -319,37 +319,37 @@ class TestTopKAPI(unittest.TestCase):
result7[0], result7[1]
])
numpy_result = numpy_topk(self.input_data, k=2)
self.assertTrue(np.allclose(paddle_result[0], numpy_result[0]))
self.assertTrue(np.allclose(paddle_result[1], numpy_result[1]))
np.testing.assert_allclose(paddle_result[0], numpy_result[0])
np.testing.assert_allclose(paddle_result[1], numpy_result[1])
numpy_result = numpy_topk(self.input_data, k=2, axis=-1)
self.assertTrue(np.allclose(paddle_result[2], numpy_result[0]))
self.assertTrue(np.allclose(paddle_result[3], numpy_result[1]))
np.testing.assert_allclose(paddle_result[2], numpy_result[0])
np.testing.assert_allclose(paddle_result[3], numpy_result[1])
numpy_result = numpy_topk(self.input_data, k=2, axis=1)
self.assertTrue(np.allclose(paddle_result[4], numpy_result[0]))
self.assertTrue(np.allclose(paddle_result[5], numpy_result[1]))
np.testing.assert_allclose(paddle_result[4], numpy_result[0])
np.testing.assert_allclose(paddle_result[5], numpy_result[1])
numpy_result = numpy_topk(self.input_data,
k=2,
axis=1,
largest=False)
self.assertTrue(np.allclose(paddle_result[6], numpy_result[0]))
self.assertTrue(np.allclose(paddle_result[7], numpy_result[1]))
np.testing.assert_allclose(paddle_result[6], numpy_result[0])
np.testing.assert_allclose(paddle_result[7], numpy_result[1])
numpy_result = numpy_topk(self.input_data,
k=2,
axis=-1,
largest=False)
self.assertTrue(np.allclose(paddle_result[8], numpy_result[0]))
self.assertTrue(np.allclose(paddle_result[9], numpy_result[1]))
np.testing.assert_allclose(paddle_result[8], numpy_result[0])
np.testing.assert_allclose(paddle_result[9], numpy_result[1])
numpy_result = numpy_topk(self.large_input_data, k=1, axis=-1)
self.assertTrue(np.allclose(paddle_result[10], numpy_result[0]))
self.assertTrue(np.allclose(paddle_result[11], numpy_result[1]))
np.testing.assert_allclose(paddle_result[10], numpy_result[0])
np.testing.assert_allclose(paddle_result[11], numpy_result[1])
sort_paddle = numpy_topk(paddle_result[12], axis=1, k=2)
numpy_result = numpy_topk(self.input_data, k=2, axis=1)
self.assertTrue(np.allclose(sort_paddle[0], numpy_result[0]))
np.testing.assert_allclose(sort_paddle[0], numpy_result[0])
def test_cases(self):
places = [core.NPUPlace(0)]
......
......@@ -157,8 +157,8 @@ class TestTrilTriuOpAPI(unittest.TestCase):
feed={"x": data},
fetch_list=[tril_out, triu_out],
)
self.assertTrue(np.allclose(tril_out, np.tril(data)))
self.assertTrue(np.allclose(triu_out, np.triu(data)))
np.testing.assert_allclose(tril_out, np.tril(data))
np.testing.assert_allclose(triu_out, np.triu(data))
def test_api_with_dygraph(self):
paddle.disable_static(fluid.NPUPlace(0))
......@@ -170,8 +170,8 @@ class TestTrilTriuOpAPI(unittest.TestCase):
x = fluid.dygraph.to_variable(data)
tril_out, triu_out = tensor.tril(x).numpy(), tensor.triu(
x).numpy()
self.assertTrue(np.allclose(tril_out, np.tril(data)))
self.assertTrue(np.allclose(triu_out, np.triu(data)))
np.testing.assert_allclose(tril_out, np.tril(data))
np.testing.assert_allclose(triu_out, np.triu(data))
def test_fluid_api(self):
paddle.enable_static()
......
......@@ -66,7 +66,7 @@ class TestTruncatedNormal(unittest.TestCase):
cpu_w = self._test(False)
npu_w = self._test(True)
self.assertTrue(np.allclose(npu_w, cpu_w))
np.testing.assert_allclose(npu_w, cpu_w)
if __name__ == '__main__':
......
......@@ -71,8 +71,11 @@ class TestNPUUniformRandomOp(OpTest):
def verify_output(self, outs):
hist, prob = self.output_hist(np.array(outs[0]))
self.assertTrue(np.allclose(hist, prob, rtol=0, atol=0.01),
"hist: " + str(hist))
np.testing.assert_allclose(hist,
prob,
rtol=0,
atol=0.01,
err_msg="hist: " + str(hist))
class TestNPUUniformRandomOpSelectedRows(unittest.TestCase):
......@@ -100,8 +103,11 @@ class TestNPUUniformRandomOpSelectedRows(unittest.TestCase):
op.run(scope, place)
self.assertEqual(out.get_tensor().shape(), [1000, 784])
hist, prob = output_hist(np.array(out.get_tensor()))
self.assertTrue(np.allclose(hist, prob, rtol=0, atol=0.01),
"hist: " + str(hist))
np.testing.assert_allclose(hist,
prob,
rtol=0,
atol=0.01,
err_msg="hist: " + str(hist))
if __name__ == "__main__":
......
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