#!/usr/bin/env python
# -*- coding: utf-8 -*-
#
# Copyright (c) 2021 Intel Corporation
#
# 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
#
#   http://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.

"""The neural engine operator mapping file."""

from .op import Operator, operator_registry
from .tensor import Tensor
import copy


# Computes softmax activations.
# tf.nn.softmax(logits, axis=None, name=None)
@operator_registry(operator_type='Softmax')
@operator_registry(operator_type='SoftmaxGraph')
class Softmax(Operator):
    """Parse the Softmax operator to the neural engine."""
    def __init__(self):
        """The init function of this operator."""
        super().__init__()

    def set_attr(self, framework, node):
        """Extract the node attr from frameworks."""
        if framework == "tensorflow":
            # last_dim = len(self._input_tensors[0].shape) - 1
            try:
                axis = self._input_tensors[1].data[0]
                self._input_tensors = [copy.deepcopy(self._input_tensors[0])]
            except BaseException:
                axis = -1
            if axis != -1:
                self._attr['axis'] = axis
        if framework == "onnxruntime":
            axis = node.attribute[0].i
        if framework == 'torch':
            self._attr['axis'] = node.inputsAt(1).toIValue()
