| # Copyright (C) 2020 Arm Limited or its affiliates. All rights reserved. |
| # |
| # SPDX-License-Identifier: Apache-2.0 |
| # |
| # 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 |
| # |
| # 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. |
| # Description: |
| # Defines custom exceptions. |
| import sys |
| |
| from .operation import Operation |
| from .tensor import Tensor |
| |
| |
| class VelaError(Exception): |
| """Base class for vela exceptions""" |
| |
| def __init__(self, data): |
| self.data = data |
| |
| def __str__(self): |
| return repr(self.data) |
| |
| |
| class InputFileError(VelaError): |
| """Raised when reading the input file results in errors""" |
| |
| def __init__(self, file_name, msg): |
| self.data = "Error reading input file {}: {}".format(file_name, msg) |
| |
| |
| class UnsupportedFeatureError(VelaError): |
| """Raised when the input file uses non-supported features that cannot be handled""" |
| |
| def __init__(self, data): |
| self.data = "The input file uses a feature that is currently not supported: {}".format(data) |
| |
| |
| class OptionError(VelaError): |
| """Raised when an incorrect command line option is used""" |
| |
| def __init__(self, option, option_value, msg): |
| self.data = "Incorrect argument to CLI option: {} {}: {}".format(option, option_value, msg) |
| |
| |
| class AllocationError(VelaError): |
| """Raised when allocation fails""" |
| |
| def __init__(self, msg): |
| self.data = msg |
| |
| |
| def OperatorError(op, msg): |
| """Called when parsing an operator results in errors""" |
| |
| assert isinstance(op, Operation) |
| |
| if op.op_index is None: |
| data = "Invalid {} (name = {}) operator in the internal representation.".format(op.type, op.name) |
| else: |
| data = "Invalid {} (op_index = {}) operator in the input network.".format(op.type, op.op_index) |
| |
| data += " {}\n".format(msg) |
| |
| data += " Input tensors:\n" |
| for idx, tens in enumerate(op.inputs): |
| if isinstance(tens, Tensor): |
| tens_name = tens.name |
| else: |
| tens_name = "Not a Tensor" |
| |
| data += " {} = {}\n".format(idx, tens_name) |
| |
| data += " Output tensors:\n" |
| for idx, tens in enumerate(op.outputs): |
| if isinstance(tens, Tensor): |
| tens_name = tens.name |
| else: |
| tens_name = "Not a Tensor" |
| |
| data += " {} = {}\n".format(idx, tens_name) |
| |
| data = data[:-1] # remove last newline |
| |
| print("Error: {}".format(data)) |
| sys.exit(1) |
| |
| |
| def TensorError(tens, msg): |
| """Called when parsing a tensor results in errors""" |
| |
| assert isinstance(tens, Tensor) |
| |
| data = "Invalid {} tensor. {}\n".format(tens.name, msg) |
| |
| data += " Driving operators:\n" |
| for idx, op in enumerate(tens.ops): |
| if isinstance(op, Operation): |
| op_type = op.type |
| op_id = op.op_index |
| else: |
| op_type = "Not an Operation" |
| op_id = "" |
| |
| data += " {} = {} ({})\n".format(idx, op_type, op_id) |
| |
| data += " Consuming operators:\n" |
| for idx, op in enumerate(tens.consumer_list): |
| if isinstance(op, Operation): |
| op_type = op.type |
| op_id = op.op_index |
| else: |
| op_type = "Not an Operation" |
| op_id = "" |
| |
| data += " {} = {} ({})\n".format(idx, op_type, op_id) |
| |
| data = data[:-1] # remove last newline |
| |
| print("Error: {}".format(data)) |
| sys.exit(1) |