def _CreatePythonApiDef(self, base_api_def, endpoint_names):
"""Creates Python ApiDef that overrides base_api_def if needed.
Args:
base_api_def: (api_def_pb2.ApiDef) base ApiDef instance.
endpoint_names: List of Python endpoint names.
Returns:
api_def_pb2.ApiDef instance with overrides for base_api_def
if module.name endpoint is different from any existing
endpoints in base_api_def. Otherwise, returns None.
"""
endpoint_names_set = set(endpoint_names)
base_endpoint_names_set = {
self._GenerateLowerCaseOpName(endpoint.name)
for endpoint in base_api_def.endpoint
}
if endpoint_names_set == base_endpoint_names_set:
return None # All endpoints are the same
api_def = api_def_pb2.ApiDef()
api_def.graph_op_name = base_api_def.graph_op_name
for endpoint_name in sorted(endpoint_names):
new_endpoint = api_def.endpoint.add()
new_endpoint.name = endpoint_name
return api_def
def get_api_def(self, op_name):
api_def_proto = api_def_pb2.ApiDef()
buf = c_api.TF_ApiDefMapGet(self._api_def_map, op_name, len(op_name))
try:
api_def_proto.ParseFromString(c_api.TF_GetBuffer(buf))
finally:
c_api.TF_DeleteBuffer(buf)
return api_def_proto
def _AddHiddenOpOverrides(self, name_to_base_api_def, api_def_map):
"""Adds ApiDef overrides to api_def_map for hidden Python ops.
Args:
name_to_base_api_def: Map from op name to base api_def_pb2.ApiDef.
api_def_map: Map from first op name character (in caps) to
api_def_pb2.ApiDefs for Python API overrides.
"""
hidden_ops = _GetHiddenOps()
for hidden_op in hidden_ops:
if hidden_op not in name_to_base_api_def:
logging.warning('Unexpected hidden op name: %s' % hidden_op)
continue
base_api_def = name_to_base_api_def[hidden_op]
if base_api_def.visibility != api_def_pb2.ApiDef.HIDDEN:
api_def = api_def_pb2.ApiDef()
api_def.graph_op_name = base_api_def.graph_op_name
api_def.visibility = api_def_pb2.ApiDef.HIDDEN
api_def_map[api_def.graph_op_name[0].upper()].op.extend(
[api_def])
def metadata():
categories = {
'Assign': 'Control',
'AvgPool': 'Pool',
'BatchNormWithGlobalNormalization': 'Normalization',
'BiasAdd': 'Layer',
'Concat': 'Tensor',
'ConcatV2': 'Tensor',
'Const': 'Constant',
'Conv2D': 'Layer',
'DepthwiseConv2dNative': 'Layer',
'Dequantize': 'Tensor',
'Elu': 'Activation',
'FusedBatchNorm': 'Normalization',
'FusedBatchNormV2': 'Normalization',
'FusedBatchNormV3': 'Normalization',
'Gather': 'Transform',
'Identity': 'Control',
'LeakyRelu': 'Activation',
'LRN': 'Normalization',
'LSTMBlockCell': 'Layer',
'MaxPool': 'Pool',
'MaxPoolV2': 'Pool',
'MaxPoolWithArgmax': 'Pool',
'Pad': 'Tensor',
'Relu': 'Activation',
'Relu6': 'Activation',
'Reshape': 'Shape',
'Sigmoid': 'Activation',
'Slice': 'Tensor',
'Softmax': 'Activation',
'Split': 'Tensor',
'Squeeze': 'Shape',
'StridedSlice': 'Tensor',
'swish_f32': 'Activation',
'Variable': 'Control',
'VariableV2': 'Control',
}
def find_multiline(line, colon):
if colon == -1:
return None
line = line[colon + 1:]
while line.startswith(' '):
line = line[1:]
if line.startswith('<<'):
line = line[2:]
return line
return None
def str_escape(text):
result = ''
for c in text:
if (c == '\n'):
result += '\\n'
elif (c == '\r'):
result += "\\r"
elif (c == '\t'):
result += "\\t"
elif (c == '\"'):
result += "\\\""
elif (c == '\''):
result += "\\'"
elif (c == '\\'):
result += "\\\\"
else:
result += c
return result
def pbtxt_from_multiline(multiline_pbtxt):
pbtxt = ''
while len(multiline_pbtxt) > 0:
index = multiline_pbtxt.find('\n')
if index == -1:
pbtxt = pbtxt + multiline_pbtxt
multiline_pbtxt = ''
break
line = multiline_pbtxt[0:index]
multiline_pbtxt = multiline_pbtxt[index + 1:]
colon = line.find(':')
end = find_multiline(line, colon)
if end == None:
pbtxt = pbtxt + line + '\n'
continue
pbtxt = pbtxt + line[0:colon + 1]
unescaped = ''
newline = False
line = ''
while len(multiline_pbtxt) > 0:
index = multiline_pbtxt.find('\n')
line = multiline_pbtxt[0:index]
multiline_pbtxt = multiline_pbtxt[index + 1:]
if line.startswith(end):
line = line[len(end):]
break
if newline:
unescaped = unescaped + '\n'
newline = True
unescaped = unescaped + line
line = ''
pbtxt = pbtxt + '\"' + str_escape(unescaped) + '\"' + line + '\n'
return pbtxt
def read_api_def_map(folder):
api_def_map = {}
file_list = os.listdir(folder)
file_list = sorted(file_list)
for filename in file_list:
if filename.endswith('.pbtxt'):
api_defs = api_def_pb2.ApiDefs()
filename = folder + '/' + filename
with open(filename) as handle:
multiline_pbtxt = handle.read()
pbtxt = pbtxt_from_multiline(multiline_pbtxt)
text_format.Merge(pbtxt, api_defs)
for api_def in api_defs.op:
api_def_map[api_def.graph_op_name] = api_def
return api_def_map
def convert_type(type):
return {'type': 'type', 'value': type}
def convert_tensor(tensor):
return {'type': 'tensor', 'value': '?'}
def convert_shape(shape):
return {'type': 'shape', 'value': '?'}
def convert_number(number):
if number == float('inf'):
return 'NaN'
if number == float('-inf'):
return '-NaN'
return number
attr_type_table = {
'type': 'type',
'list(type)': 'type[]',
'bool': 'boolean',
'int': 'int64',
'list(int)': 'int64[]',
'float': 'float32',
'list(float)': 'float32[]',
'string': 'string',
'list(string)': 'string[]',
'shape': 'shape',
'list(shape)': 'shape[]',
'tensor': 'tensor',
'func': 'function',
'list(func)': 'function[]'
}
def convert_attr_type(type):
if type in attr_type_table:
return attr_type_table[type]
print(type)
return type
def convert_attr_value(attr_value):
if attr_value.HasField('list'):
list = []
attr_value_list = attr_value.list
if len(attr_value_list.s) > 0:
for s in attr_value_list.s:
list.append(s.decode('utf8'))
if len(attr_value_list.i) > 0:
for i in attr_value_list.i:
list.append(i)
if len(attr_value_list.f) > 0:
for f in attr_value_list.f:
list.append(convert_number(f))
if len(attr_value_list.type) > 0:
for type in attr_value_list.type:
list.append(convert_type(type))
if len(list) == 0:
for _, value in attr_value_list.ListFields():
if len(value) > 0:
raise Exception()
return list
if attr_value.HasField('s'):
return attr_value.s.decode('utf8')
if attr_value.HasField('i'):
return attr_value.i
if attr_value.HasField('f'):
return convert_number(attr_value.f)
if attr_value.HasField('b'):
return attr_value.b
if attr_value.HasField('type'):
return convert_type(attr_value.type)
if attr_value.HasField('tensor'):
return convert_tensor(attr_value.tensor)
if attr_value.HasField('shape'):
return convert_shape(attr_value.shape)
raise Exception()
_TYPE_TO_STRING = {
types_pb2.DataType.DT_HALF: "float16",
types_pb2.DataType.DT_FLOAT: "float32",
types_pb2.DataType.DT_DOUBLE: "float64",
types_pb2.DataType.DT_INT32: "int32",
types_pb2.DataType.DT_UINT8: "uint8",
types_pb2.DataType.DT_UINT16: "uint16",
types_pb2.DataType.DT_UINT32: "uint32",
types_pb2.DataType.DT_UINT64: "uint64",
types_pb2.DataType.DT_INT16: "int16",
types_pb2.DataType.DT_INT8: "int8",
types_pb2.DataType.DT_STRING: "string",
types_pb2.DataType.DT_COMPLEX64: "complex64",
types_pb2.DataType.DT_COMPLEX128: "complex128",
types_pb2.DataType.DT_INT64: "int64",
types_pb2.DataType.DT_BOOL: "bool",
types_pb2.DataType.DT_QINT8: "qint8",
types_pb2.DataType.DT_QUINT8: "quint8",
types_pb2.DataType.DT_QINT16: "qint16",
types_pb2.DataType.DT_QUINT16: "quint16",
types_pb2.DataType.DT_QINT32: "qint32",
types_pb2.DataType.DT_BFLOAT16: "bfloat16",
types_pb2.DataType.DT_RESOURCE: "resource",
types_pb2.DataType.DT_VARIANT: "variant",
types_pb2.DataType.DT_HALF_REF: "float16_ref",
types_pb2.DataType.DT_FLOAT_REF: "float32_ref",
types_pb2.DataType.DT_DOUBLE_REF: "float64_ref",
types_pb2.DataType.DT_INT32_REF: "int32_ref",
types_pb2.DataType.DT_UINT32_REF: "uint32_ref",
types_pb2.DataType.DT_UINT8_REF: "uint8_ref",
types_pb2.DataType.DT_UINT16_REF: "uint16_ref",
types_pb2.DataType.DT_INT16_REF: "int16_ref",
types_pb2.DataType.DT_INT8_REF: "int8_ref",
types_pb2.DataType.DT_STRING_REF: "string_ref",
types_pb2.DataType.DT_COMPLEX64_REF: "complex64_ref",
types_pb2.DataType.DT_COMPLEX128_REF: "complex128_ref",
types_pb2.DataType.DT_INT64_REF: "int64_ref",
types_pb2.DataType.DT_UINT64_REF: "uint64_ref",
types_pb2.DataType.DT_BOOL_REF: "bool_ref",
types_pb2.DataType.DT_QINT8_REF: "qint8_ref",
types_pb2.DataType.DT_QUINT8_REF: "quint8_ref",
types_pb2.DataType.DT_QINT16_REF: "qint16_ref",
types_pb2.DataType.DT_QUINT16_REF: "quint16_ref",
types_pb2.DataType.DT_QINT32_REF: "qint32_ref",
types_pb2.DataType.DT_BFLOAT16_REF: "bfloat16_ref",
types_pb2.DataType.DT_RESOURCE_REF: "resource_ref",
types_pb2.DataType.DT_VARIANT_REF: "variant_ref",
}
def format_data_type(data_type):
if data_type in _TYPE_TO_STRING:
return _TYPE_TO_STRING[data_type]
raise Exception()
def format_attribute_value(value):
if type(value
) is dict and 'type' in value and 'value' in value and value[
'type'] == 'type':
return format_data_type(value['value'])
if type(value) is str:
return value
if value == True:
return 'true'
if value == False:
return 'false'
raise Exception()
tensorflow_repo_dir = os.path.join(os.path.dirname(__file__),
'../third_party/source/tensorflow')
api_def_map = read_api_def_map(
os.path.join(tensorflow_repo_dir, 'tensorflow/core/api_def/base_api'))
input_file = os.path.join(tensorflow_repo_dir,
'tensorflow/core/ops/ops.pbtxt')
ops_list = op_def_pb2.OpList()
with open(input_file) as input_handle:
text_format.Merge(input_handle.read(), ops_list)
json_root = []
for op in ops_list.op:
# print(op.name)
json_schema = {}
json_schema['name'] = op.name
if op.name in categories:
json_schema['category'] = categories[op.name]
api_def = api_def_pb2.ApiDef()
if op.name in api_def_map:
api_def = api_def_map[op.name]
# if op.deprecation.version != 0:
# print('[' + op.name + ']')
# print(op.deprecation.version)
# print(op.deprecation.explanation)
api_def_attr_map = {}
for attr in api_def.attr:
api_def_attr_map[attr.name] = attr
api_def_in_arg_map = {}
for in_arg in api_def.in_arg:
api_def_in_arg_map[in_arg.name] = in_arg
api_def_out_arg_map = {}
for out_arg in api_def.out_arg:
api_def_out_arg_map[out_arg.name] = out_arg
if api_def.summary:
json_schema['summary'] = api_def.summary
if api_def.description:
json_schema['description'] = api_def.description
for attr in op.attr:
if not 'attributes' in json_schema:
json_schema['attributes'] = []
json_attribute = {}
json_attribute['name'] = attr.name
attr_type = convert_attr_type(attr.type)
if attr_type:
json_attribute['type'] = attr_type
else:
del json_attribute['type']
if attr.name in api_def_attr_map:
api_def_attr = api_def_attr_map[attr.name]
if api_def_attr.description:
json_attribute['description'] = api_def_attr.description
if attr.has_minimum:
json_attribute['minimum'] = attr.minimum
if attr.HasField('allowed_values'):
allowed_values = convert_attr_value(attr.allowed_values)
description = json_attribute[
'description'] + ' ' if 'description' in json_attribute else ''
description = description + 'Must be one of the following: ' + ', '.join(
list(
map(lambda x: "`" + format_attribute_value(x) + "`",
allowed_values))) + '.'
json_attribute['description'] = description
if attr.HasField('default_value'):
default_value = convert_attr_value(attr.default_value)
json_attribute['default'] = default_value
json_schema['attributes'].append(json_attribute)
for input_arg in op.input_arg:
if not 'inputs' in json_schema:
json_schema['inputs'] = []
json_input = {}
json_input['name'] = input_arg.name
if input_arg.name in api_def_in_arg_map:
api_def_in_arg = api_def_in_arg_map[input_arg.name]
if api_def_in_arg.description:
json_input['description'] = api_def_in_arg.description
if input_arg.number_attr:
json_input['numberAttr'] = input_arg.number_attr
if input_arg.type:
json_input['type'] = input_arg.type
if input_arg.type_attr:
json_input['typeAttr'] = input_arg.type_attr
if input_arg.type_list_attr:
json_input['typeListAttr'] = input_arg.type_list_attr
if input_arg.is_ref:
json_input['isRef'] = True
json_schema['inputs'].append(json_input)
for output_arg in op.output_arg:
if not 'outputs' in json_schema:
json_schema['outputs'] = []
json_output = {}
json_output['name'] = output_arg.name
if output_arg.name in api_def_out_arg_map:
api_def_out_arg = api_def_out_arg_map[output_arg.name]
if api_def_out_arg.description:
json_output['description'] = api_def_out_arg.description
if output_arg.number_attr:
json_output['numberAttr'] = output_arg.number_attr
if output_arg.type:
json_output['type'] = output_arg.type
elif output_arg.type_attr:
json_output['typeAttr'] = output_arg.type_attr
elif output_arg.type_list_attr:
json_output['typeListAttr'] = output_arg.type_list_attr
if output_arg.is_ref:
json_output['isRef'] = True
json_schema['outputs'].append(json_output)
json_root.append(json_schema)
json_file = os.path.join(os.path.dirname(__file__),
'../source/tf-metadata.json')
with io.open(json_file, 'w', newline='') as fout:
json_data = json.dumps(json_root, sort_keys=False, indent=2)
for line in json_data.splitlines():
line = line.rstrip()
fout.write(line)
fout.write('\n')
def metadata():
categories = {
'Const': 'Constant',
'Conv2D': 'Layer',
'BiasAdd': 'Layer',
'DepthwiseConv2dNative': 'Layer',
'Relu': 'Activation',
'Relu6': 'Activation',
'Elu': 'Activation',
'Softmax': 'Activation',
'Sigmoid': 'Activation',
'LRN': 'Normalization',
'MaxPool': 'Pool',
'MaxPoolV2': 'Pool',
'AvgPool': 'Pool',
'Reshape': 'Shape',
'Squeeze': 'Shape',
'ConcatV2': 'Tensor',
'Split': 'Tensor',
'Dequantize': 'Tensor',
'Identity': 'Control',
'Variable': 'Control',
'VariableV2': 'Control',
'Assign': 'Control',
'BatchNormWithGlobalNormalization': 'Normalization',
'FusedBatchNorm': 'Normalization',
# 'VariableV2':
# 'Assign':
# 'BiasAdd':
}
def find_multiline(line, colon):
if colon == -1:
return None
line = line[colon + 1:]
while line.startswith(' '):
line = line[1:]
if line.startswith('<<'):
line = line[2:]
return line
return None
def str_escape(text):
result = ''
for c in text:
if (c == '\n'):
result += '\\n'
elif (c == '\r'):
result += "\\r"
elif (c == '\t'):
result += "\\t"
elif (c == '\"'):
result += "\\\""
elif (c == '\''):
result += "\\'"
elif (c == '\\'):
result += "\\\\"
else:
result += c
return result
def pbtxt_from_multiline(multiline_pbtxt):
pbtxt = ''
while len(multiline_pbtxt) > 0:
index = multiline_pbtxt.find('\n')
if index == -1:
pbtxt = pbtxt + multiline_pbtxt
multiline_pbtxt = ''
break
line = multiline_pbtxt[0:index]
multiline_pbtxt = multiline_pbtxt[index + 1:]
colon = line.find(':')
end = find_multiline(line, colon)
if end == None:
pbtxt = pbtxt + line + '\n'
continue
pbtxt = pbtxt + line[0:colon + 1]
unescaped = ''
newline = False
line = ''
while len(multiline_pbtxt) > 0:
index = multiline_pbtxt.find('\n')
line = multiline_pbtxt[0:index]
multiline_pbtxt = multiline_pbtxt[index + 1:]
if line.startswith(end):
line = line[len(end):]
break
if newline:
unescaped = unescaped + '\n'
newline = True
unescaped = unescaped + line
line = ''
pbtxt = pbtxt + '\"' + str_escape(unescaped) + '\"' + line + '\n'
return pbtxt
def read_api_def_map(folder):
api_def_map = {}
file_list = os.listdir(folder)
file_list = sorted(file_list)
for filename in file_list:
api_defs = api_def_pb2.ApiDefs()
filename = folder + '/' + filename
with open(filename) as handle:
multiline_pbtxt = handle.read()
pbtxt = pbtxt_from_multiline(multiline_pbtxt)
text_format.Merge(pbtxt, api_defs)
for api_def in api_defs.op:
api_def_map[api_def.graph_op_name] = api_def
return api_def_map
def convert_type(type):
return {'type': 'type', 'value': type}
def convert_tensor(tensor):
return {'type': 'tensor', 'value': '?'}
def convert_shape(shape):
return {'type': 'shape', 'value': '?'}
def convert_number(number):
if number == float('inf'):
return 'NaN'
if number == float('-inf'):
return '-NaN'
return number
attr_type_table = {
'type': 'type',
'list(type)': 'type[]',
'bool': 'boolean',
'int': 'int64',
'list(int)': 'int64[]',
'float': 'float32',
'list(float)': 'float32[]',
'string': 'string',
'list(string)': 'string[]',
'shape': 'shape',
'list(shape)': 'shape[]',
'tensor': 'tensor',
'func': 'function',
'list(func)': 'function[]'
}
def convert_attr_type(type):
if type in attr_type_table:
return attr_type_table[type]
print(type)
return type
def convert_attr_value(attr_value):
if attr_value.HasField('list'):
list = []
attr_value_list = attr_value.list
if len(attr_value_list.s) > 0:
for s in attr_value_list.s:
list.append(s.decode('utf8'))
if len(attr_value_list.i) > 0:
for i in attr_value_list.i:
list.append(i)
if len(attr_value_list.f) > 0:
for f in attr_value_list.f:
list.append(convert_number(f))
if len(attr_value_list.type) > 0:
for type in attr_value_list.type:
list.append(convert_type(type))
if len(list) == 0:
for _, value in attr_value_list.ListFields():
if len(value) > 0:
raise Exception()
return list
if attr_value.HasField('s'):
return attr_value.s.decode('utf8')
if attr_value.HasField('i'):
return attr_value.i
if attr_value.HasField('f'):
return convert_number(attr_value.f)
if attr_value.HasField('b'):
return attr_value.b
if attr_value.HasField('type'):
return convert_type(attr_value.type)
if attr_value.HasField('tensor'):
return convert_tensor(attr_value.tensor)
if attr_value.HasField('shape'):
return convert_shape(attr_value.shape)
raise Exception()
tensorflow_repo_dir = os.path.join(os.path.dirname(__file__),
'../third_party/src/tensorflow')
api_def_map = read_api_def_map(
os.path.join(tensorflow_repo_dir, 'tensorflow/core/api_def/base_api'))
input_file = os.path.join(tensorflow_repo_dir,
'tensorflow/core/ops/ops.pbtxt')
ops_list = op_def_pb2.OpList()
with open(input_file) as input_handle:
text_format.Merge(input_handle.read(), ops_list)
json_root = []
for op in ops_list.op:
# print(op.name)
json_schema = {}
if op.name in categories:
json_schema['category'] = categories[op.name]
api_def = api_def_pb2.ApiDef()
if op.name in api_def_map:
api_def = api_def_map[op.name]
# if op.deprecation.version != 0:
# print('[' + op.name + ']')
# print(op.deprecation.version)
# print(op.deprecation.explanation)
api_def_attr_map = {}
for attr in api_def.attr:
api_def_attr_map[attr.name] = attr
api_def_in_arg_map = {}
for in_arg in api_def.in_arg:
api_def_in_arg_map[in_arg.name] = in_arg
api_def_out_arg_map = {}
for out_arg in api_def.out_arg:
api_def_out_arg_map[out_arg.name] = out_arg
if api_def.summary:
json_schema['summary'] = api_def.summary
if api_def.description:
json_schema['description'] = api_def.description
for attr in op.attr:
if not 'attributes' in json_schema:
json_schema['attributes'] = []
json_attribute = {}
json_attribute['name'] = attr.name
attr_type = convert_attr_type(attr.type)
if attr_type:
json_attribute['type'] = attr_type
else:
del json_attribute['type']
if attr.name in api_def_attr_map:
api_def_attr = api_def_attr_map[attr.name]
if api_def_attr.description:
json_attribute['description'] = api_def_attr.description
if attr.has_minimum:
json_attribute['minimum'] = attr.minimum
if attr.HasField('allowed_values'):
json_attribute['allowedValues'] = convert_attr_value(
attr.allowed_values)
if attr.HasField('default_value'):
json_attribute['default'] = convert_attr_value(
attr.default_value)
json_schema['attributes'].append(json_attribute)
for input_arg in op.input_arg:
if not 'inputs' in json_schema:
json_schema['inputs'] = []
json_input = {}
json_input['name'] = input_arg.name
if input_arg.name in api_def_in_arg_map:
api_def_in_arg = api_def_in_arg_map[input_arg.name]
if api_def_in_arg.description:
json_input['description'] = api_def_in_arg.description
if input_arg.number_attr:
json_input['numberAttr'] = input_arg.number_attr
if input_arg.type:
json_input['type'] = input_arg.type
if input_arg.type_attr:
json_input['typeAttr'] = input_arg.type_attr
if input_arg.type_list_attr:
json_input['typeListAttr'] = input_arg.type_list_attr
if input_arg.is_ref:
json_input['isRef'] = True
json_schema['inputs'].append(json_input)
for output_arg in op.output_arg:
if not 'outputs' in json_schema:
json_schema['outputs'] = []
json_output = {}
json_output['name'] = output_arg.name
if output_arg.name in api_def_out_arg_map:
api_def_out_arg = api_def_out_arg_map[output_arg.name]
if api_def_out_arg.description:
json_output['description'] = api_def_out_arg.description
if output_arg.number_attr:
json_output['numberAttr'] = output_arg.number_attr
if output_arg.type:
json_output['type'] = output_arg.type
elif output_arg.type_attr:
json_output['typeAttr'] = output_arg.type_attr
elif output_arg.type_list_attr:
json_output['typeListAttr'] = output_arg.type_list_attr
if output_arg.is_ref:
json_output['isRef'] = True
json_schema['outputs'].append(json_output)
json_root.append({'name': op.name, 'schema': json_schema})
json_file = os.path.join(os.path.dirname(__file__),
'../src/tf-metadata.json')
with io.open(json_file, 'w', newline='') as fout:
json_data = json.dumps(json_root, sort_keys=True, indent=2)
for line in json_data.splitlines():
line = line.rstrip()
if sys.version_info[0] < 3:
line = unicode(line)
fout.write(line)
fout.write('\n')
'../third_party/tensorflow/tensorflow/core/api_def/base_api')
input_file = '../third_party/tensorflow/tensorflow/core/ops/ops.pbtxt'
ops_list = op_def_pb2.OpList()
with open(input_file) as input_handle:
text_format.Merge(input_handle.read(), ops_list)
json_root = []
for op in ops_list.op:
# print(op.name)
json_schema = {}
if op.name in categories:
json_schema['category'] = categories[op.name]
api_def = api_def_pb2.ApiDef()
if op.name in api_def_map:
api_def = api_def_map[op.name]
# if op.deprecation.version != 0:
# print('[' + op.name + ']')
# print(op.deprecation.version)
# print(op.deprecation.explanation)
api_def_attr_map = {}
for attr in api_def.attr:
api_def_attr_map[attr.name] = attr
api_def_in_arg_map = {}
for in_arg in api_def.in_arg:
api_def_in_arg_map[in_arg.name] = in_arg
api_def_out_arg_map = {}
for out_arg in api_def.out_arg:
api_def_out_arg_map[out_arg.name] = out_arg
