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247 lines
8.2 KiB
247 lines
8.2 KiB
import paddle.v2.framework.core as core
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import paddle.v2.framework.proto.op_proto_pb2 as op_proto_pb2
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import paddle.v2.framework.proto.op_desc_pb2 as op_desc_pb2
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import paddle.v2.framework.proto.attr_type_pb2 as attr_type_pb2
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import cStringIO
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def get_all_op_protos():
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"""
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Get all registered op proto from Paddle C++
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:return: list of OpProto
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"""
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protostrs = core.get_all_op_protos()
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ret_values = []
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for pbstr in protostrs:
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op_proto = op_proto_pb2.OpProto.FromString(str(pbstr))
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ret_values.append(op_proto)
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return ret_values
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class OpDescCreationMethod(object):
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"""
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A Functor object to convert user input(use key word args) to OpDesc based on
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OpProto.
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:param op_proto: The OpProto object.
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:type op_proto: op_proto_pb2.OpProto
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"""
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def __init__(self, op_proto):
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if not isinstance(op_proto, op_proto_pb2.OpProto):
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raise TypeError("Argument should be OpProto")
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self.__op_proto__ = op_proto
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def __call__(self, *args, **kwargs):
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"""
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Convert user input to OpDesc. Only key-word args are supported.
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:return: OpDesc based on user input
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:rtype: op_desc_pb2.OpDesc
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"""
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if len(args) != 0:
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raise ValueError("Only keyword arguments is supported by Paddle")
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op_desc = op_desc_pb2.OpDesc()
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# Inputs
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ipts, ipt_format, _ = OpDescCreationMethod.extract_input_or_output(
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"input", kwargs, self.__op_proto__.inputs)
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op_desc.inputs.extend(ipts)
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if ipt_format is not None:
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op_desc.attrs.extend([ipt_format])
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# Outputs
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outs, out_format, tmp_index = OpDescCreationMethod.extract_input_or_output(
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"output", kwargs, self.__op_proto__.outputs)
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op_desc.outputs.extend(outs)
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if out_format is not None:
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op_desc.attrs.extend([out_format])
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if len(tmp_index) != 0:
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tmp_index_attr = op_desc.attrs.add()
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tmp_index_attr.type = attr_type_pb2.INTS
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tmp_index_attr.name = "temporary_index"
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tmp_index_attr.ints.extend(tmp_index)
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# Types
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op_desc.type = self.__op_proto__.type
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# Attrs
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for attr in self.__op_proto__.attrs:
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if attr.generated:
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continue
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user_defined_attr = kwargs.get(attr.name, None)
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if user_defined_attr is not None:
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new_attr = op_desc.attrs.add()
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new_attr.name = attr.name
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new_attr.type = attr.type
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if attr.type == attr_type_pb2.INT:
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new_attr.i = user_defined_attr
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elif attr.type == attr_type_pb2.FLOAT:
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new_attr.f = user_defined_attr
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elif attr.type == attr_type_pb2.STRING:
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new_attr.s = user_defined_attr
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elif attr.type == attr_type_pb2.INTS:
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new_attr.ints.extend(user_defined_attr)
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elif attr.type == attr_type_pb2.FLOATS:
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new_attr.floats.extend(user_defined_attr)
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elif attr.type == attr_type_pb2.STRINGS:
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new_attr.strings.extend(user_defined_attr)
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else:
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raise NotImplementedError("Not support attribute type " +
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attr.type)
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return op_desc
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@staticmethod
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def extract_input_or_output(in_out, kwargs, meta):
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"""
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Extract input variable names or output variable names from key-word
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arguments, which base on VarProtos.
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:param in_out: "input" or "output"
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:param kwargs: key-word arguments that user inputted.
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:param meta: a list of VarProto
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:return: The three object will be return. The variable names. The
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input_format or output_format attribute(None if the input or output is
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not multiple). The temporary variable index list.
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"""
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multiple = OpDescCreationMethod.any_is_true((m.multiple for m in meta))
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tmp_index = []
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retv = []
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if multiple:
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var_format = op_desc_pb2.AttrDesc()
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var_format.type = attr_type_pb2.INTS
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var_format.name = "%s_format" % in_out
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var_format.ints.append(0)
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for var in meta:
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var_name = var.name
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if var.temporary:
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var_name = [core.var_names.temp()]
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tmp_index.append(len(retv))
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else:
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var_name = kwargs.get(var_name, [])
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if not isinstance(var_name, list):
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var_name = [var_name]
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retv.extend(var_name)
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var_format.ints.append(len(var_name) + var_format.ints[-1])
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return retv, var_format, tmp_index
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else:
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for var in meta:
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if var.temporary:
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retv.append(kwargs.get(var.name, core.var_names.temp()))
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tmp_index.append(len(retv))
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else:
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retv.append(kwargs.get(var.name, core.var_names.empty()))
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return retv, None, tmp_index
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@staticmethod
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def any_is_true(generator):
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"""
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Reduce a bool array to one. If any of them is True, then return True.
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"""
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for flag in generator:
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if flag:
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return True
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return False
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def get_docstring_from_op_proto(op_proto):
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"""
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Generate docstring from a OpProto
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:param op_proto: a OpProto instance.
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:type op_proto: op_proto_pb2.OpProto
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:return: docstring
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"""
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if not isinstance(op_proto, op_proto_pb2.OpProto):
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raise TypeError("Input must be OpProto")
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f = cStringIO.StringIO()
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f.write(op_proto.comment)
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f.write("\n")
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def __append_param__(name, comment, type):
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# Maybe replace the following line with template engine is better.
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f.write(":param ")
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f.write(name)
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f.write(": ")
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f.write(comment)
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f.write("\n")
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f.write(":type ")
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f.write(name)
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f.write(": ")
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f.write(type)
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f.write("\n")
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for ipt in op_proto.inputs:
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__append_param__(ipt.name, ipt.comment, "list | basestr"
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if ipt.multiple else "basestr")
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temp_var_prefix = \
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"This is a temporary variable. It does not have to set by user. "
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for opt in op_proto.outputs:
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__append_param__(opt.name, opt.comment if not opt.temporary else
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temp_var_prefix + opt.comment, "list | basestr"
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if opt.multiple else "basestr")
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for attr in op_proto.attrs:
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attr_type = None
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if attr.type == attr_type_pb2.INT:
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attr_type = "int"
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elif attr.type == attr_type_pb2.FLOAT:
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attr_type = "float"
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elif attr.type == attr_type_pb2.STRING:
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attr_type = "basestr"
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elif attr.type == attr_type_pb2.INTS:
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attr_type = "list of int"
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elif attr.type == attr_type_pb2.FLOATS:
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attr_type = "list of float"
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elif attr.type == attr_type_pb2.STRINGS:
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attr_type = "list of basestr"
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if attr_type is None:
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raise RuntimeError("Not supported attribute type " + attr.type)
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__append_param__(attr.name, attr.comment, attr_type)
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return f.getvalue()
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def create_op_creation_method(op_proto):
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"""
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Generate op creation method for an OpProto
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"""
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method = OpDescCreationMethod(op_proto)
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def __impl__(*args, **kwargs):
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opdesc = method(*args, **kwargs)
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return core.Operator.create(opdesc.SerializeToString())
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__impl__.__doc__ = get_docstring_from_op_proto(op_proto)
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return __impl__
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class OpCreationsHolder(object):
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"""
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A object will holds all op creation methods.
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Use `op_creations.xxx_op` to access them.
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"""
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pass
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op_creations = OpCreationsHolder()
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def __bootstrap__():
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"""
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Bootstrap function for this module. It will dynamic create all op creation
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methods in runtime.
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"""
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for op_proto in get_all_op_protos():
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func = create_op_creation_method(op_proto)
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func.__name__ = str(op_proto.type)
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setattr(op_creations, func.__name__, func)
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__bootstrap__()
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