add

tools/test_generator.py

+# Copyright (c) 2018 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 __future__ import print_function
+import re
+import functools
+import warnings
+import string
+
+from six.moves import cStringIO
+from paddle.fluid.proto import framework_pb2
+from paddle.fluid.framework import OpProtoHolder, Variable
+from paddle.fluid.layer_helper import LayerHelper
+
+
+def _convert_(name):
+    """
+    Formatting.
+
+    Args:
+       name: The name/alias
+
+    This function takes in a name and converts it to a standard format of
+    group1_group2. Where as per the regular expression, group1 can have
+    alphabets and numbers and group2 has capital alphabets.
+
+    """
+    s1 = re.sub('(.)([A-Z][a-z]+)', r'\1_\2', name)
+    return re.sub('([a-z0-9])([A-Z])', r'\1_\2', s1).lower()
+
+
+def _get_inputs(op_type):
+    op_proto = OpProtoHolder.instance().get_op_proto(op_type)
+    inputs = dict()
+    for ipt in op_proto.inputs:
+        inputs[ipt.name] = ""
+
+
+def _get_outputs(op_type):
+    op_proto = OpProtoHolder.instance().get_op_proto(op_type)
+    outputs = {}
+    for ipt in op_proto.outputs:
+        outputs[ipt.name] = ""
+
+
+def get_input_comments(op_type):
+    return ""
+
+
+def get_output_comments(op_type):
+    return ""
+
+
+def get_func_args(op_type):
+    return ""
+
+
+def get_inputs(op_type):
+    return ""
+
+
+def get_outputs(op_type):
+    return ""
+
+
+def get_op_py(op_type):
+    input_comments = get_input_comments(op_type)
+    output_comments = get_output_comments(op_type)
+    args = get_func_args(op_type)
+    inputs = get_inputs(op_type)
+    outputs = get_outputs(op_type)
+
+    code = """
+\@templatedoc()
+def {op_type}({args}):
+    \"\"\"
+    {op_type}
+    
+    Args:
+        {input_comments}
+    Returns:
+        {output_comments}
+    \"\"\"
+    helper.append_op(
+        type='{op_type}',
+        {inputs},
+        {outputs})    
+""".format(
+        input_comments=input_comments,
+        output_comments=output_comments,
+        args=args,
+        op_type=op_type,
+        inputs=inputs,
+        outputs=outputs)
+
+    return code
+
+
+print(get_op_py("uniform_random_batch_size_like"))
+#get_meta("linear_chain_crf")