Merge pull request #234 from ooooo-create/fix_rrelu

[Accuracy diff No.48-49] Fix accuracy diff for rrelu API

Author: wanghuancoder

tester/api_config/2_paddle_only_random/random_calculation.txt

@@ -25604,4 +25604,9 @@ paddle.put_along_axis(Tensor([6, 8000],"float32"), Tensor([6, 799],"int64"), Ten
 paddle.put_along_axis(Tensor([7, 8000],"float32"), Tensor([7, 799],"int64"), Tensor([7, 799],"float32"), 1, )
 paddle.put_along_axis(Tensor([8, 8000],"float32"), Tensor([8, 799],"int64"), Tensor([8, 799],"float32"), 1, )
 paddle.put_along_axis(Tensor([9, 8000],"float32"), Tensor([9, 799],"int64"), Tensor([9, 799],"float32"), 1, )
-paddle.topk(Tensor([128, 1000],"float16"), k=5, )
+paddle.topk(Tensor([128, 1000],"float16"), k=5, )
+paddle.nn.functional.rrelu(Tensor([1, 2, 3, 4],"float64"), lower=0.05, upper=0.25, training=True, )
+paddle.nn.functional.rrelu(Tensor([],"float32"), )
+paddle.nn.functional.rrelu(Tensor([2, 3, 4, 5],"float32"), 0.3, 0.300000009, training=True, )
+paddle.nn.functional.rrelu(Tensor([2, 3, 4, 5],"float64"), 0.3, 0.300000009, training=True, )
+paddle.nn.functional.rrelu(Tensor([2, 3, 4, 5],"float16"), 0.3, 0.300000009, training=True, )

tester/api_config/5_accuracy/accuracy_7.txt

@@ -153424,9 +153424,7 @@ paddle.nn.functional.relu6(x=Tensor([4],"float64"), )
 paddle.nn.functional.rrelu(Tensor([1, 2, 3, 4],"float64"), 0.05, 0.25, training=False, )
 paddle.nn.functional.rrelu(Tensor([1, 2, 3, 4],"float64"), 0.1, 0.33, training=False, )
 paddle.nn.functional.rrelu(Tensor([2, 3, 4, 5],"float32"), 0.1, 0.3, training=False, )
-paddle.nn.functional.rrelu(Tensor([2, 3, 4, 5],"float32"), 0.3, 0.300000009, training=True, )
 paddle.nn.functional.rrelu(Tensor([2, 3, 4, 5],"float64"), 0.1, 0.3, training=False, )
-paddle.nn.functional.rrelu(Tensor([2, 3, 4, 5],"float64"), 0.3, 0.300000009, training=True, )
 paddle.nn.functional.selu(Tensor([2, 2],"float32"), 1.0507009873554805, 1.6732632423543772, None, )
 paddle.nn.functional.selu(Tensor([2, 2],"float64"), 1.0507009873554805, 1.6732632423543772, None, )
 paddle.nn.functional.selu(Tensor([3, 3, 3],"float64"), 1.0507009873554805, 0, None, )

tester/api_config/5_accuracy/accuracy_cpu_kernel.txt

@@ -38158,7 +38158,6 @@ paddle.nn.functional.relu6(Tensor([64, 906, 7, 7],"float16"), None, )
 paddle.nn.functional.relu6(Tensor([64, 96, 56, 56],"float16"), None, )
 paddle.nn.functional.relu6(Tensor([64, 972, 7, 7],"float16"), None, )
 paddle.nn.functional.rrelu(Tensor([2, 3, 4, 5],"float16"), 0.1, 0.3, training=False, )
-paddle.nn.functional.rrelu(Tensor([2, 3, 4, 5],"float16"), 0.3, 0.300000009, training=True, )
 paddle.nn.functional.sigmoid(Tensor([1, 3, 5, 2, 4],"float16"), )
 paddle.nn.functional.sigmoid(Tensor([10, 499, 4],"float16"), None, )
 paddle.nn.functional.sigmoid(Tensor([100, 200, 304],"float16"), )

tester/api_config/5_accuracy/accuracy_gpu_error.txt

@@ -19940,8 +19940,6 @@ paddle.logit(Tensor([],"float32"), )
 paddle.nextafter(Tensor([],"float32"), Tensor([2, 3, 4],"float32"), )
 paddle.nn.functional.cosine_similarity(Tensor([23, 12, 1],"float32"), Tensor([23, 1, 10],"float32"), axis=2, eps=1e-06, )
 paddle.nn.functional.cosine_similarity(Tensor([5, 1, 3],"float64"), Tensor([1, 3],"float64"), axis=0, eps=1e-08, )
-paddle.nn.functional.rrelu(Tensor([1, 2, 3, 4],"float64"), lower=0.05, upper=0.25, training=True, )
-paddle.nn.functional.rrelu(Tensor([],"float32"), )
 paddle.reciprocal(Tensor([16, 1, 640, 640],"float16"), )
 paddle.reciprocal(Tensor([4, 1, 640, 640],"float16"), )
 paddle.reciprocal(Tensor([8, 1, 640, 640],"float16"), )

tester/base.py

@@ -67,6 +67,7 @@
         # "paddle.nn.functional.feature_alpha_dropout",
         # "paddle.incubate.nn.functional.fused_multi_head_attention", # If parameter "dropout_rate=0.5, attn_dropout_rate=0.5 (default value)" is not equal to 0.0 or 1.0, the result involves random calculation.
         # "paddle.nn.functional.scaled_dot_product_attention", # If parameter "dropout_p=0.0" is not equal to 0.0 or 1.0, the result involves random calculation.
+        # "paddle.nn.functional.rrelu", # If parameter "training=True" is set, the result involves random calculation.
     ]
 )