Add benchmark for log_loss op

api/dynamic_tests_v2/log_loss.py

@@ -0,0 +1,40 @@
+#   Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+from common_import import *
+
+
+class LogLossConfig(APIConfig):
+    def __init__(self):
+        super(LogLossConfig, self).__init__("log_loss")
+        self.run_torch = False
+        self.feed_spec = [{"range": [-1, 1]}, {"range": [-1, 1]}]
+
+
+class PDLogLoss(PaddleDynamicAPIBenchmarkBase):
+    def build_graph(self, config):
+        input = self.variable(
+            name='input', shape=config.input_shape, dtype=config.input_dtype)
+        label = self.variable(
+            name='label', shape=config.label_shape, dtype=config.label_dtype)
+        result = paddle.nn.functional.log_loss(
+            input=input, label=label, epsilon=config.epsilon)
+        self.feed_list = [input, label]
+        self.fetch_list = [result]
+        if config.backward:
+            self.append_gradients(result, [input])
+
+
+if __name__ == '__main__':
+    test_main(pd_dy_obj=PDLogLoss(), config=LogLossConfig())

api/tests_v2/configs/log_loss.json

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+[{
+    "op": "log_loss",
+    "param_info": {
+        "epsilon": {
+            "type": "float",
+            "value": "0.0001"
+        },
+        "label": {
+            "dtype": "float32",
+            "shape": "[30720L, 1L]",
+            "type": "Variable"
+        },
+        "input": {
+            "dtype": "float32",
+            "shape": "[30720L, 1L]",
+            "type": "Variable"
+        }
+    },
+    "repeat": 10000
+}, {
+    "op": "log_loss",
+    "param_info": {
+        "epsilon": {
+            "type": "float",
+            "value": "0.001"
+        },
+        "label": {
+            "dtype": "float32",
+            "shape": "[40960L, 1L]",
+            "type": "Variable"
+        },
+        "input": {
+            "dtype": "float32",
+            "shape": "[40960L, 1L]",
+            "type": "Variable"
+        }
+    },
+    "repeat": 10000
+}]