#!/usr/bin/env python
# ******************************************************************************
# Copyright 2022 Brainchip Holdings Ltd.
#
# 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
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# ******************************************************************************
"""Input layer size reshaping for Keras/CNN2SNN Sequential models.
"""
from keras import Sequential, Input
from .clone import clone_model_with_weights
[docs]def reshape(model_keras, input_x, input_y):
""" Rescales the model by changing its input size.
Args:
model_keras (:obj:`tf.keras.Model`): Keras model to rescale
input_x (int): desired model input first dimension
input_y (int): desired model input second dimension
Returns:
keras.Model: the rescaled model
"""
# The reshape function is restricted to Sequential models only
assert isinstance(model_keras, Sequential)
# Create the desired input
input_shape = (input_x, input_y, model_keras.input.shape[-1])
new_input = Input(input_shape)
# Clone the model and replace input layer
clone = clone_model_with_weights(model_keras, input_tensors=new_input)
return clone