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Diffstat (limited to 'ethosu/vela/tosa_supported_operators.py')
-rw-r--r-- | ethosu/vela/tosa_supported_operators.py | 85 |
1 files changed, 85 insertions, 0 deletions
diff --git a/ethosu/vela/tosa_supported_operators.py b/ethosu/vela/tosa_supported_operators.py new file mode 100644 index 00000000..c87d653a --- /dev/null +++ b/ethosu/vela/tosa_supported_operators.py @@ -0,0 +1,85 @@ +# Copyright (C) 2021 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: +# The TosaSupportedOperators class which is a collection of all supported operators and parameter checks. +from collections import defaultdict + +from .data_type import DataType +from .operation import Op +from .supported_operators_util import docstring_format_args +from .supported_operators_util import list_formatter +from .tosa_mapping import optype_to_tosa_op_type + + +class TosaSupportedOperators: + # TODO currently sparsely populated + # Categorised lists of supported operators + convolution_ops = set((Op.Conv2DBias,)) + convolution_like_ops = convolution_ops + mac_main_ops = convolution_like_ops + + type_conversion_ops = set((Op.Rescale,)) + relu_ops = set((Op.Clip, Op.ReluN,)) + activation_ops = relu_ops + + npu_post_ops = activation_ops + supported_operators = mac_main_ops | type_conversion_ops | npu_post_ops + + # Supported data types + # TODO will differ compared to TensorFlow Lite, currently set to the same + supported_op_dtypes = set((DataType.uint8, DataType.int8, DataType.int16, DataType.int32)) + + def __init__(self): + # Setup the generic constraints. Note: the order matters + self.generic_constraints = [] + self.generic_constraints.append(TosaSupportedOperators.constraint_tens_dtype) + + # Setup specific constraints. Note: the order matters + self.specific_constraints = defaultdict(list) + + def is_operator_supported(self, op): + ext_type = optype_to_tosa_op_type(op.type) + if op.type not in TosaSupportedOperators.supported_operators: + if op.type not in (Op.Placeholder, Op.SubgraphInput, Op.Const): + print(f"Info: {ext_type} '{op.name}' is not a NPU op") + return False + + for constraint in self.generic_constraints + self.specific_constraints[op.type]: + valid, extra = constraint(op) + if not valid: + print(f"Warning: {ext_type} '{op.name}' is not supported on the NPU") + print(f" - {constraint.__doc__}") + if extra: + print(f" {extra}") + return False + + return True + + # TODO this function is the same for TensorFlow Lite, but input might differ + @classmethod + @docstring_format_args([list_formatter(supported_op_dtypes)]) + def constraint_tens_dtype(cls, op): + "Tensors must be of type: {}" + valid = True + extra = [] + tensors = [tens for tens in op.get_ifm_ifm2_weights_ofm() if tens] + if not tensors: + tensors = [tens for tens in op.inputs if tens] + for tens in tensors: + if tens.dtype not in cls.supported_op_dtypes: + valid = False + extra.append(f"Tensor '{tens.name}' has data type: {tens.dtype}") + return valid, ", ".join(extra) |