Update test precision from fp32 to fp64 (#21805)

python/paddle/fluid/tests/unittests/test_mean_op.py

@@ -25,7 +25,7 @@ from paddle.fluid import Program, program_guard
 class TestMeanOp(OpTest):
     def setUp(self):
         self.op_type = "mean"
-        self.dtype = np.float32
+        self.dtype = np.float64
         self.init_dtype_type()
         self.inputs = {'X': np.random.random((10, 10)).astype(self.dtype)}
         self.outputs = {'Out': np.mean(self.inputs["X"])}

python/paddle/fluid/tests/unittests/test_mine_hard_examples_op.py

@@ -59,13 +59,13 @@ class TestMineHardExamplesOp(OpTest):
         self.sample_size = 0
         self.mining_type = "max_negative"
         self.cls_loss = np.array([[0.1, 0.1, 0.3],
-                                  [0.3, 0.1, 0.1]]).astype('float32')
+                                  [0.3, 0.1, 0.1]]).astype('float64')
 
         self.loc_loss = np.array([[0.1, 0.2, 0.3],
-                                  [0.3, 0.4, 0.1]]).astype('float32')
+                                  [0.3, 0.4, 0.1]]).astype('float64')
 
         self.match_dis = np.array([[0.2, 0.4, 0.8],
-                                   [0.1, 0.9, 0.3]]).astype('float32')
+                                   [0.1, 0.9, 0.3]]).astype('float64')
 
         self.match_indices = np.array([[0, -1, -1],
                                        [-1, 0, -1]]).astype('int32')
@@ -83,10 +83,10 @@ class TestMineHardExamplesOpHardExample(TestMineHardExamplesOp):
         self.sample_size = 2
 
         self.cls_loss = np.array([[0.5, 0.1, 0.3],
-                                  [0.3, 0.1, 0.1]]).astype('float32')
+                                  [0.3, 0.1, 0.1]]).astype('float64')
 
         self.loc_loss = np.array([[0.2, 0.2, 0.3],
-                                  [0.3, 0.1, 0.2]]).astype('float32')
+                                  [0.3, 0.1, 0.2]]).astype('float64')
 
         self.match_indices = np.array([[0, -1, -1],
                                        [-1, 0, -1]]).astype('int32')

python/paddle/fluid/tests/unittests/test_mul_op.py

@@ -25,7 +25,7 @@ from paddle.fluid import Program, program_guard
 class TestMulOp(OpTest):
     def setUp(self):
         self.op_type = "mul"
-        self.dtype = np.float32
+        self.dtype = np.float64
         self.init_dtype_type()
         self.inputs = {
             'X': np.random.random((2, 5)).astype(self.dtype),
@@ -69,7 +69,7 @@ class TestMulOpError(unittest.TestCase):
 class TestMulOp2(OpTest):
     def setUp(self):
         self.op_type = "mul"
-        self.dtype = np.float32
+        self.dtype = np.float64
         self.init_dtype_type()
         self.inputs = {
             'X': np.random.random((3, 4, 4, 3)).astype(self.dtype),

python/paddle/fluid/tests/unittests/test_multiplex_op.py

@@ -26,10 +26,10 @@ class TestMultiplexOp(OpTest):
         index = np.arange(0, rows).astype('int32')
         np.random.shuffle(index)
         index = np.reshape(index, (rows, 1))
-        ins1 = np.random.random((rows, 25)).astype("float32")
-        ins2 = np.random.random((rows, 25)).astype("float32")
-        ins3 = np.random.random((rows, 25)).astype("float32")
-        ins4 = np.random.random((rows, 25)).astype("float32")
+        ins1 = np.random.random((rows, 25)).astype("float64")
+        ins2 = np.random.random((rows, 25)).astype("float64")
+        ins3 = np.random.random((rows, 25)).astype("float64")
+        ins4 = np.random.random((rows, 25)).astype("float64")
         self.inputs = {
             'Ids': index,
             'X': [('x1', ins1), ('x2', ins2), ('x3', ins3), ('x4', ins4)]

python/paddle/fluid/tests/unittests/test_nearest_interp_op.py

@@ -79,7 +79,7 @@ class TestNearestInterpOp(OpTest):
         self.data_layout = 'NCHW'
         self.init_test_case()
         self.op_type = "nearest_interp"
-        input_np = np.random.random(self.input_shape).astype("float32")
+        input_np = np.random.random(self.input_shape).astype("float64")
 
         if self.data_layout == "NCHW":
             in_h = self.input_shape[2]
@@ -340,11 +340,11 @@ class TestNearestInterpOp_attr_tensor(OpTest):
             'align_corners': self.align_corners,
         }
 
-        input_np = np.random.random(self.input_shape).astype("float32")
+        input_np = np.random.random(self.input_shape).astype("float64")
         self.inputs = {'X': input_np}
 
         if self.scale_by_1Dtensor:
-            self.inputs['Scale'] = np.array([self.scale]).astype("float32")
+            self.inputs['Scale'] = np.array([self.scale]).astype("float64")
         elif self.scale > 0:
             out_h = int(self.input_shape[2] * self.scale)
             out_w = int(self.input_shape[3] * self.scale)

python/paddle/fluid/tests/unittests/test_pixel_shuffle.py

@@ -25,7 +25,7 @@ class TestPixelShuffle(OpTest):
         n, c, h, w = 2, 9, 4, 4
         up_factor = 3
         shape = [n, c, h, w]
-        x = np.random.random(shape).astype("float32")
+        x = np.random.random(shape).astype("float64")
         new_shape = (n, c // (up_factor * up_factor), up_factor, up_factor, h,
                      w)
         # reshape to (num,output_channel,upscale_factor,upscale_factor,h,w)

python/paddle/fluid/tests/unittests/test_pool2d_op.py

@@ -39,7 +39,7 @@ def max_pool2D_forward_naive(x,
                              ceil_mode=False,
                              exclusive=True,
                              adaptive=False,
-                             data_type=np.float32):
+                             data_type=np.float64):
     N, C, H, W = x.shape
     if global_pool == 1:
         ksize = [H, W]
@@ -79,7 +79,7 @@ def avg_pool2D_forward_naive(x,
                              ceil_mode=False,
                              exclusive=True,
                              adaptive=False,
-                             data_type=np.float32):
+                             data_type=np.float64):
     N, C, H, W = x.shape
     if global_pool == 1:
         ksize = [H, W]
@@ -320,7 +320,7 @@ class TestPool2D_Op(OpTest):
         self.use_cudnn = False
 
     def init_data_type(self):
-        self.dtype = np.float32
+        self.dtype = np.float64
 
     def init_pool_type(self):
         self.pool_type = "avg"

python/paddle/fluid/tests/unittests/test_pool3d_op.py

@@ -209,7 +209,7 @@ class TestPool3d_Op(OpTest):
     def setUp(self):
         self.op_type = "pool3d"
         self.init_kernel_type()
-        self.dtype = np.float32
+        self.dtype = np.float64
         self.init_test_case()
         self.padding_algorithm = "EXPLICIT"
         self.init_paddings()

python/paddle/fluid/tests/unittests/test_pool_max_op.py

@@ -140,11 +140,11 @@ class TestMaxPoolWithIndex_Op(OpTest):
         self.init_global()
         self.init_adaptive()
 
-        input = np.random.random(self.shape).astype("float32")
+        input = np.random.random(self.shape).astype("float64")
         output, mask = self.pool_forward_naive(input, self.ksize, self.strides,
                                                self.paddings, self.global_pool,
                                                self.adaptive)
-        output = output.astype("float32")
+        output = output.astype("float64")
         mask = mask.astype("int32")
 
         self.attrs = {

python/paddle/fluid/tests/unittests/test_psroi_pool_op.py

@@ -47,7 +47,7 @@ class TestPSROIPoolOp(OpTest):
         self.pooled_height = 2
         self.pooled_width = 2
 
-        self.x = np.random.random(self.x_dim).astype('float32')
+        self.x = np.random.random(self.x_dim).astype('float64')
 
     def make_rois(self):
         rois = []
@@ -67,7 +67,7 @@ class TestPSROIPoolOp(OpTest):
                 roi = [bno, x1, y1, x2, y2]
                 rois.append(roi)
         self.rois_num = len(rois)
-        self.rois = np.array(rois).astype('float32')
+        self.rois = np.array(rois).astype('float64')
 
     def calc_psroi_pool(self):
         output_shape = (self.rois_num, self.output_channels, self.pooled_height,
@@ -117,7 +117,7 @@ class TestPSROIPoolOp(OpTest):
                         bin_area = (hend - hstart) * (wend - wstart)
                         out_data[i, c, ph, pw] = 0. if is_empty else (
                             out_sum / float(bin_area))
-        self.outs = out_data.astype('float32')
+        self.outs = out_data.astype('float64')
 
     def setUp(self):
         self.op_type = 'psroi_pool'

python/paddle/fluid/tests/unittests/test_reverse_op.py

@@ -21,7 +21,7 @@ from op_test import OpTest
 
 class TestReverseOp(OpTest):
     def initTestCase(self):
-        self.x = np.random.random((3, 40)).astype('float32')
+        self.x = np.random.random((3, 40)).astype('float64')
         self.axis = [0]
 
     def setUp(self):
@@ -43,25 +43,25 @@ class TestReverseOp(OpTest):
 
 class TestCase0(TestReverseOp):
     def initTestCase(self):
-        self.x = np.random.random((3, 40)).astype('float32')
+        self.x = np.random.random((3, 40)).astype('float64')
         self.axis = [1]
 
 
 class TestCase1(TestReverseOp):
     def initTestCase(self):
-        self.x = np.random.random((3, 40)).astype('float32')
+        self.x = np.random.random((3, 40)).astype('float64')
         self.axis = [0, 1]
 
 
 class TestCase2(TestReverseOp):
     def initTestCase(self):
-        self.x = np.random.random((3, 4, 10)).astype('float32')
+        self.x = np.random.random((3, 4, 10)).astype('float64')
         self.axis = [0, 2]
 
 
 class TestCase3(TestReverseOp):
     def initTestCase(self):
-        self.x = np.random.random((3, 4, 10)).astype('float32')
+        self.x = np.random.random((3, 4, 10)).astype('float64')
         self.axis = [1, 2]
 
 

python/paddle/fluid/tests/unittests/test_roi_align_op.py

@@ -50,16 +50,16 @@ class TestROIAlignOp(OpTest):
         self.pooled_width = 2
         self.sampling_ratio = -1
 
-        self.x = np.random.random(self.x_dim).astype('float32')
+        self.x = np.random.random(self.x_dim).astype('float64')
 
     def pre_calc(self, x_i, roi_xmin, roi_ymin, roi_bin_grid_h, roi_bin_grid_w,
                  bin_size_h, bin_size_w):
         count = roi_bin_grid_h * roi_bin_grid_w
         bilinear_pos = np.zeros(
             [self.channels, self.pooled_height, self.pooled_width, count, 4],
-            np.float32)
+            np.float64)
         bilinear_w = np.zeros(
-            [self.pooled_height, self.pooled_width, count, 4], np.float32)
+            [self.pooled_height, self.pooled_width, count, 4], np.float64)
         for ph in range(self.pooled_width):
             for pw in range(self.pooled_height):
                 c = 0
@@ -109,7 +109,7 @@ class TestROIAlignOp(OpTest):
     def calc_roi_align(self):
         self.out_data = np.zeros(
             (self.rois_num, self.channels, self.pooled_height,
-             self.pooled_width)).astype('float32')
+             self.pooled_width)).astype('float64')
 
         for i in range(self.rois_num):
             roi = self.rois[i]
@@ -157,7 +157,7 @@ class TestROIAlignOp(OpTest):
                 roi = [bno, x1, y1, x2, y2]
                 rois.append(roi)
         self.rois_num = len(rois)
-        self.rois = np.array(rois).astype("float32")
+        self.rois = np.array(rois).astype("float64")
 
     def setUp(self):
         self.op_type = "roi_align"

python/paddle/fluid/tests/unittests/test_roi_pool_op.py

@@ -51,7 +51,7 @@ class TestROIPoolOp(OpTest):
         self.pooled_height = 2
         self.pooled_width = 2
 
-        self.x = np.random.random(self.x_dim).astype('float32')
+        self.x = np.random.random(self.x_dim).astype('float64')
 
     def calc_roi_pool(self):
         out_data = np.zeros((self.rois_num, self.channels, self.pooled_height,
@@ -103,7 +103,7 @@ class TestROIPoolOp(OpTest):
                                     argmax_data[i, c, ph,
                                                 pw] = h * self.width + w
 
-        self.outs = out_data.astype('float32')
+        self.outs = out_data.astype('float64')
         self.argmaxes = argmax_data.astype('int64')
 
     def make_rois(self):
@@ -125,7 +125,7 @@ class TestROIPoolOp(OpTest):
                 roi = [bno, x1, y1, x2, y2]
                 rois.append(roi)
         self.rois_num = len(rois)
-        self.rois = np.array(rois).astype("float32")
+        self.rois = np.array(rois).astype("float64")
 
     def setUp(self):
         self.op_type = "roi_pool"

python/paddle/fluid/tests/unittests/test_scatter_nd_op.py

@@ -66,9 +66,9 @@ class TestScatterNdAddSimpleOp(OpTest):
     def setUp(self):
         self.op_type = "scatter_nd_add"
         #ref_np = np.array([0, 1, 2, 3, 4, 5, 6, 7, 8]).astype("float32")
-        ref_np = np.random.random([100]).astype("float32")
+        ref_np = np.random.random([100]).astype("float64")
         index_np = np.random.randint(0, 100, [100, 1]).astype("int32")
-        updates_np = np.random.random([100]).astype("float32")
+        updates_np = np.random.random([100]).astype("float64")
         expect_np = numpy_scatter_nd_add(ref_np.copy(), index_np, updates_np)
         #expect_np = [ 0. 23. 12. 14.  4. 17.  6.  7.  8.] 
 
@@ -89,10 +89,10 @@ class TestScatterNdAddWithEmptyIndex(OpTest):
 
     def setUp(self):
         self.op_type = "scatter_nd_add"
-        ref_np = np.array([[65, 17], [-14, -25]]).astype("float32")
+        ref_np = np.array([[65, 17], [-14, -25]]).astype("float64")
         index_np = np.array([[], []]).astype("int32")
         updates_np = np.array([[[-1, -2], [1, 2]],
-                               [[3, 4], [-3, -4]]]).astype("float32")
+                               [[3, 4], [-3, -4]]]).astype("float64")
 
         expect_np = numpy_scatter_nd_add(ref_np.copy(), index_np, updates_np)
         #expect_np = [[67, 19], [-16, -27]]
@@ -115,12 +115,12 @@ class TestScatterNdAddWithHighRankSame(OpTest):
     def setUp(self):
         self.op_type = "scatter_nd_add"
         shape = (10, 9, 8, 1, 15)
-        ref_np = np.random.rand(*shape).astype("float32")
+        ref_np = np.random.rand(*shape).astype("float64")
         index_np = np.vstack(
             [np.random.randint(
                 0, s, size=150) for s in shape]).T.astype("int32")
         update_shape = judge_update_shape(ref_np, index_np)
-        updates_np = np.random.rand(*update_shape).astype("float32")
+        updates_np = np.random.rand(*update_shape).astype("float64")
         expect_np = numpy_scatter_nd_add(ref_np.copy(), index_np, updates_np)
 
         self.inputs = {'X': ref_np, 'Index': index_np, 'Updates': updates_np}

python/paddle/fluid/tests/unittests/test_selu_op.py

@@ -24,7 +24,7 @@ class SeluTest(OpTest):
     def setUp(self):
         self.op_type = "selu"
         self.x_shape = [3, 5, 5, 10]
-        self.dtype = np.float32
+        self.dtype = np.float64
         self.init_x_shape()
         self.init_dtype()