still trying

config.json

@@ -0,0 +1 @@
+{"name": "sequential", "layers": [{"module": "keras.layers", "class_name": "InputLayer", "config": {"batch_input_shape": [null, 224, 224, 3], "dtype": "float32", "sparse": false, "ragged": false, "name": "input_1"}, "registered_name": null}, {"module": "keras.layers", "class_name": "GlobalAveragePooling2D", "config": {"name": "global_average_pooling2d", "trainable": true, "dtype": "float32", "data_format": "channels_last", "keepdims": false}, "registered_name": null, "build_config": {"input_shape": [null, 224, 224, 3]}}, {"module": "keras.layers", "class_name": "Dense", "config": {"name": "dense", "trainable": true, "dtype": "float32", "units": 101, "activation": "relu", "use_bias": true, "kernel_initializer": {"module": "keras.initializers", "class_name": "GlorotUniform", "config": {"seed": null}, "registered_name": null}, "bias_initializer": {"module": "keras.initializers", "class_name": "Zeros", "config": {}, "registered_name": null}, "kernel_regularizer": null, "bias_regularizer": null, "activity_regularizer": null, "kernel_constraint": null, "bias_constraint": null}, "registered_name": null, "build_config": {"input_shape": [null, 3]}}, {"module": "keras.layers", "class_name": "Activation", "config": {"name": "activation", "trainable": true, "dtype": "float32", "activation": "softmax"}, "registered_name": null, "build_config": {"input_shape": [null, 101]}}]}

foodTrain.pd/fingerprint.pb

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:bbe2501aab7aaf280a1eff941aeba11932ef2429fb15cbd64d10b479192d3ac7
+oid sha256:e21de62f86c685651878dd4291005dd5ac999899defd5d0024ce10d9d73d0a17
 size 57

food_train.py

@@ -3,6 +3,7 @@ import matplotlib.pyplot as plt
 import numpy as np 
 import tensorflow as tf
 from PIL import Image
+import json
 
 from tensorflow import keras
 import tensorflow_datasets as tfds
@@ -50,3 +51,5 @@ model.fit(train_data, epochs=5, verbose = 2, batch_size=101)
 model.evaluate(test_data, batch_size=101)
 
 model.save("foodTrain.pd")
+with open("config.json", "w") as outfile:
+    json.dump(model.get_config(), outfile)