op.py 7.4 KB
Newer Older
Y
Yu Yang 已提交
1
import paddle.v2.framework.core as core
2
import paddle.v2.framework.proto.attr_type_pb2 as attr_type_pb2
Y
Yu Yang 已提交
3 4
import paddle.v2.framework.proto.op_desc_pb2 as op_desc_pb2
import paddle.v2.framework.proto.op_proto_pb2 as op_proto_pb2
Y
Yu Yang 已提交
5 6 7


def get_all_op_protos():
8 9 10 11
    """
    Get all registered op proto from Paddle C++
    :return: list of OpProto
    """
Y
Yu Yang 已提交
12 13 14
    protostrs = core.get_all_op_protos()
    ret_values = []
    for pbstr in protostrs:
Y
Yu Yang 已提交
15
        op_proto = op_proto_pb2.OpProto.FromString(str(pbstr))
Y
Yu Yang 已提交
16 17
        ret_values.append(op_proto)
    return ret_values
18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157


class OpDescCreationMethod(object):
    """
    A Functor object to convert user input(use key word args) to OpDesc based on
    OpProto.
    
    :param op_proto: The OpProto object.
    :type op_proto: op_proto_pb2.OpProto
    """

    def __init__(self, op_proto):
        if not isinstance(op_proto, op_proto_pb2.OpProto):
            raise TypeError("Argument should be OpProto")
        self.__op_proto__ = op_proto

    def __call__(self, *args, **kwargs):
        """
        Convert user input to OpDesc. Only key-word args are supported. 
        :return: OpDesc based on user input
        :rtype: op_desc_pb2.OpDesc
        """
        if len(args) != 0:
            raise ValueError("Only keyword arguments is supported by Paddle")
        op_desc = op_desc_pb2.OpDesc()

        # Inputs
        ipts, ipt_format, _ = OpDescCreationMethod.extract_input_or_output(
            "input", kwargs, self.__op_proto__.inputs)
        op_desc.inputs.extend(ipts)
        if ipt_format is not None:
            op_desc.attrs.extend([ipt_format])

        # Outputs
        outs, out_format, tmp_index = OpDescCreationMethod.extract_input_or_output(
            "output", kwargs, self.__op_proto__.outputs)
        op_desc.outputs.extend(outs)
        if out_format is not None:
            op_desc.attrs.extend([out_format])
        if len(tmp_index) != 0:
            tmp_index_attr = op_desc.attrs.add()
            tmp_index_attr.type = attr_type_pb2.INTS
            tmp_index_attr.name = "temporary_index"
            tmp_index_attr.ints.extend(tmp_index)

        # Types
        op_desc.type = self.__op_proto__.type

        # Attrs
        for attr in self.__op_proto__.attrs:
            if attr.generated:
                continue
            user_defined_attr = kwargs.get(attr.name, None)
            if user_defined_attr is not None:
                new_attr = op_desc.attrs.add()
                new_attr.name = attr.name
                new_attr.type = attr.type
                if attr.type == attr_type_pb2.INT:
                    new_attr.i = user_defined_attr
                elif attr.type == attr_type_pb2.FLOAT:
                    new_attr.f = user_defined_attr
                elif attr.type == attr_type_pb2.STRING:
                    new_attr.s = user_defined_attr
                elif attr.type == attr_type_pb2.INTS:
                    new_attr.ints.extend(user_defined_attr)
                elif attr.type == attr_type_pb2.FLOATS:
                    new_attr.floats.extend(user_defined_attr)
                elif attr.type == attr_type_pb2.STRINGS:
                    new_attr.strings.extend(user_defined_attr)
                else:
                    raise NotImplementedError("Not support attribute type " +
                                              attr.type)

        return op_desc

    @staticmethod
    def extract_input_or_output(in_out, kwargs, meta):
        """
        Extract input variable names or output variable names from key-word 
        arguments, which base on VarProtos.
        
        :param in_out: "input" or "output"
        :param kwargs: key-word arguments that user inputted.
        :param meta: a list of VarProto
        :return: The three object will be return. The variable names. The 
        input_format or output_format attribute(None if the input or output is 
        not multiple). The temporary variable index list.
        """
        multiple = OpDescCreationMethod.any_is_true((m.multiple for m in meta))
        tmp_index = []
        retv = []
        if multiple:
            var_format = op_desc_pb2.AttrDesc()
            var_format.type = attr_type_pb2.INTS
            var_format.name = "%s_format" % in_out
            var_format.ints.append(0)

            for var in meta:
                var_name = var.name

                if var.temporary:
                    var_name = [core.var_names.temp()]
                    tmp_index.append(len(retv))
                else:
                    var_name = kwargs.get(var_name, [])
                if not isinstance(var_name, list):
                    var_name = [var_name]
                retv.extend(var_name)
                var_format.ints.append(len(var_name) + var_format.ints[-1])
            return retv, var_format, tmp_index
        else:
            for var in meta:
                if var.temporary:
                    retv.append(kwargs.get(var.name, core.var_names.temp()))
                    tmp_index.append(len(retv))
                else:
                    retv.append(kwargs.get(var.name, core.var_names.empty()))
            return retv, None, tmp_index

    @staticmethod
    def any_is_true(generator):
        """
        Reduce a bool array to one. If any of them is True, then return True.
        """
        for flag in generator:
            if flag:
                return True
        return False


def create_op_creation_method(op_proto):
    """
    Generate op creation method for an OpProto
    """
    method = OpDescCreationMethod(op_proto)

    def __impl__(*args, **kwargs):
        opdesc = method(*args, **kwargs)
        return core.Operator.create(opdesc.SerializeToString())

158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173
    return {
        'method': __impl__,
        'name': op_proto.type,
        'all_inputs': [var.name for var in op_proto.inputs],
        'all_outputs': [var.name for var in op_proto.outputs],
        'all_attrs': [attr.name for attr in op_proto.attrs],
        'all_no_temp_outputs':
        [var.name for var in op_proto.outputs if not var.temporary]
    }


class OperatorFactory(object):
    def __init__(self):
        self.op_methods = dict()
        for op_proto in get_all_op_protos():
            method = create_op_creation_method(op_proto)
Y
Yu Yang 已提交
174
            self.op_methods[method['name']] = method
Y
Yu Yang 已提交
175

176 177 178 179 180 181 182 183 184 185 186
    def __call__(self, *args, **kwargs):
        if 'type' in kwargs:
            if len(args) != 0:
                raise ValueError("All Paddle argument should be key-word "
                                 "argument except type")
            t = kwargs.pop('type')
        else:
            if len(args) != 1:
                raise ValueError("All Paddle argument should be key-word "
                                 "argument except type")
            t = args[0]
187

188
        return self.get_op_creation_info(t)['method'](**kwargs)
189

Y
Yu Yang 已提交
190 191 192
    def types(self):
        return self.op_methods.keys()

193 194 195 196
    def get_op_creation_info(self, t):
        if t not in self.op_methods:
            raise ValueError("operator %s is not registered", t)
        return self.op_methods.get(t)
197

198 199
    def get_op_input_names(self, type):
        return self.get_op_creation_info(type)['all_inputs']
200

201 202
    def get_op_output_names(self, type):
        return self.get_op_creation_info(type)['all_outputs']
203

204 205
    def get_op_attr_names(self, type):
        return self.get_op_creation_info(type)['all_attrs']
206

207 208
    def get_op_no_temp_output_names(self, type):
        return self.get_op_creation_info(type)['all_no_temp_outputs']
209 210


211
Operator = OperatorFactory()  # Default global factory