Generally, my input data is a list of array with different shape (same first axis, sample numbers), it seems that tf-explain does not work properly on my pretrained tensorflow keras model. The error msg looks like below:
Traceback (most recent call last):
File "deepST_generate_map.py", line 349, in <module>
grid = explainer.explain(data, model, class_index=0)
File "/home/zcx/anaconda3/envs/tfpy/lib/python3.7/site-packages/tf_explain/core/grad_cam.py", line 55, in explain
model, images, layer_name, class_index, use_guided_grads
File "/home/zcx/anaconda3/envs/tfpy/lib/python3.7/site-packages/tf_explain/core/grad_cam.py", line 115, in get_gradients_and_filters
inputs = tf.cast(images, tf.float32)
File "/home/zcx/anaconda3/envs/tfpy/lib/python3.7/site-packages/tensorflow/python/util/dispatch.py", line 201, in wrapper
return target(*args, **kwargs)
File "/home/zcx/anaconda3/envs/tfpy/lib/python3.7/site-packages/tensorflow/python/ops/math_ops.py", line 964, in cast
x = ops.convert_to_tensor(x, name="x")
File "/home/zcx/anaconda3/envs/tfpy/lib/python3.7/site-packages/tensorflow/python/profiler/trace.py", line 163, in wrapped
return func(*args, **kwargs)
File "/home/zcx/anaconda3/envs/tfpy/lib/python3.7/site-packages/tensorflow/python/framework/ops.py", line 1540, in convert_to_tensor
ret = conversion_func(value, dtype=dtype, name=name, as_ref=as_ref)
File "/home/zcx/anaconda3/envs/tfpy/lib/python3.7/site-packages/tensorflow/python/framework/constant_op.py", line 339, in _constant_tensor_conversion_function
return constant(v, dtype=dtype, name=name)
File "/home/zcx/anaconda3/envs/tfpy/lib/python3.7/site-packages/tensorflow/python/framework/constant_op.py", line 265, in constant
allow_broadcast=True)
File "/home/zcx/anaconda3/envs/tfpy/lib/python3.7/site-packages/tensorflow/python/framework/constant_op.py", line 276, in _constant_impl
return _constant_eager_impl(ctx, value, dtype, shape, verify_shape)
File "/home/zcx/anaconda3/envs/tfpy/lib/python3.7/site-packages/tensorflow/python/framework/constant_op.py", line 301, in _constant_eager_impl
t = convert_to_eager_tensor(value, ctx, dtype)
File "/home/zcx/anaconda3/envs/tfpy/lib/python3.7/site-packages/tensorflow/python/framework/constant_op.py", line 98, in convert_to_eager_tensor
return ops.EagerTensor(value, ctx.device_name, dtype)
ValueError: Can't convert non-rectangular Python sequence to Tensor.
Generally, my input data is a list of array with different shape (same first axis, sample numbers), it seems that
tf-explaindoes not work properly on my pretrained tensorflow keras model. The error msg looks like below: