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# MATLAB Deep Learning Toolbox Converter for TensorFlow Models.
# 13-Aug-2025 21:15:39
import TextStoryAI.model
import os
def load_model(load_weights=True, debug=False):
m = model.create_model()
if load_weights:
loadWeights(m, debug=debug)
return m
## Utility functions:
import tensorflow as tf
import h5py
def loadWeights(model, filename=os.path.join(__package__, "weights.h5"), debug=False):
with h5py.File(filename, 'r') as f:
# Every layer is an h5 group. Ignore non-groups (such as /0)
for g in f:
if isinstance(f[g], h5py.Group):
group = f[g]
layerName = group.attrs['Name']
numVars = int(group.attrs['NumVars'])
if debug:
print("layerName:", layerName)
print(" numVars:", numVars)
# Find the layer index from its namevar
layerIdx = layerNum(model, layerName)
layer = model.layers[layerIdx]
if debug:
print(" layerIdx=", layerIdx)
# Every weight is an h5 dataset in the layer group. Read the weights
# into a list in the correct order
weightList = [0]*numVars
for d in group:
dataset = group[d]
varName = dataset.attrs['Name']
shp = intList(dataset.attrs['Shape'])
weightNum = int(dataset.attrs['WeightNum'])
# Read the weight and put it into the right position in the list
if debug:
print(" varName:", varName)
print(" shp:", shp)
print(" weightNum:", weightNum)
weightList[weightNum] = tf.constant(dataset[()], shape=shp)
# Assign the weights into the layer
for w in range(numVars):
if debug:
print("Copying variable of shape:")
print(weightList[w].shape)
layer.variables[w].assign(weightList[w])
if debug:
print("Assignment successful.")
print("Set variable value:")
print(layer.variables[w])
# Finalize layer state
if hasattr(layer, 'finalize_state'):
layer.finalize_state()
def layerNum(model, layerName):
# Returns the index to the layer
layers = model.layers
for i in range(len(layers)):
if layerName==layers[i].name:
return i
print("")
print("WEIGHT LOADING FAILED. MODEL DOES NOT CONTAIN LAYER WITH NAME: ", layerName)
print("")
return -1
def intList(myList):
# Converts a list of numbers into a list of ints.
return list(map(int, myList))
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