checking.py

import numpy as np
import tensorflow as tf

# Load the TFLite model and allocate tensors.
interpreter = tf.lite.Interpreter(model_path="/Users/younglimmm/PycharmProjects/FindingIdeaAI/converted_ver2_model.tflite")
interpreter.allocate_tensors()

# Get input and output tensors.
input_details = interpreter.get_input_details()
output_details = interpreter.get_output_details()

# Test the model on random input data.
input_shape = input_details[0]['shape']
output_shape = output_details[0]['shape']

print(input_shape)

input_data = np.array(np.random.random_sample(input_shape), dtype=np.float32)
interpreter.set_tensor(input_details[0]['index'], input_data)

interpreter.invoke()

# The function `get_tensor()` returns a copy of the tensor data.
# Use `tensor()` in order to get a pointer to the tensor.
output_data = interpreter.get_tensor(output_details[0]['index'])
print(output_data.shape)

print(tf.__version__)

print(tf.config.list_physical_devices('GPU'))