about environment set (tf version?)

[hongyinjie]

environment set1: (use tf2， follow the environment.ipynb)
OS debian stretch/sid
Python 3.7.4
NumPy 1.17.2
Pandas 1.0.4
Matplotlib 3.2.1
OpenCV 3.4.3
TensorFlow 2.0.0-beta1
Keras 2.2.4-tf
tqdm 4.46.1
imageio 2.6.1

environment set2:
OS debian stretch/sid
Python 3.7.5
NumPy 1.18.0
Pandas 0.25.3
Matplotlib 3.2.1
OpenCV 3.4.3
TensorFlow 1.15.0
Keras 2.2.4-tf
tqdm 4.41.1
imageio 2.8.0

when use set1:
it run wrong in PriorUtil:

Traceback (most recent call last):
File "/mnt/downloads/github_src/ssd_detectors/SSD_predict.py", line 40, in
prior_util = PriorUtil(model)
File "/mnt/downloads/github_src/ssd_detectors/ssd_utils.py", line 353, in init
self.update_priors()
File "/mnt/downloads/github_src/ssd_detectors/ssd_utils.py", line 375, in update_priors
m.compute_priors()
File "/mnt/downloads/github_src/ssd_detectors/ssd_utils.py", line 193, in compute_priors
linx = np.array([(0.5 + i) for i in range(map_w)]) * step_x
TypeError: 'NoneType' object cannot be interpreted as an integer

Traceback (most recent call last):
File "/mnt/downloads/github_src/ssd_detectors/SL_end2end_predict.py", line 41, in
prior_util = PriorUtil(model)
File "/mnt/downloads/github_src/ssd_detectors/sl_utils.py", line 45, in init
if i > 0 and np.all(np.array(previous_map_size) != np.array(map_size)*2):
TypeError: unsupported operand type(s) for *: 'NoneType' and 'int'

when use set2
SSD_predict and SL_predict
it works well.

but alse print that:

---

layer missing zero_padding2d_5
file []

---

what is wrong...

when use set2 run

---

layer missing reshape_1
file []
something went wrong bidirectional_1
model [[512, 1024], [256, 1024], [1024], [512, 1024], [256, 1024], [1024]]
file [(512, 768), (256, 768), (768,), (512, 768), (256, 768), (768,)]
Layer weight shape (512, 1024) not compatible with provided weight shape (512, 768)
layer missing bidirectional_2
file [(512, 768), (256, 768), (768,), (512, 768), (256, 768), (768,)]
layer missing label_input
file []
layer missing input_length
file []
layer missing label_length
file []
layer missing ctc
file []

---

Traceback (most recent call last):
File "/mnt/downloads/github_src/ssd_detectors/SL_end2end_predict.py", line 152, in
res_crnn = crnn_model.predict(words)
File "/home/hyj/anaconda3/envs/py37tf15/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/training.py", line 908, in predict
use_multiprocessing=use_multiprocessing)
File "/home/hyj/anaconda3/envs/py37tf15/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/training_arrays.py", line 723, in predict
callbacks=callbacks)
File "/home/hyj/anaconda3/envs/py37tf15/lib/python3.7/site-packages/tensorflow_core/python/keras/engine/training_arrays.py", line 394, in model_iteration
batch_outs = f(ins_batch)
File "/home/hyj/anaconda3/envs/py37tf15/lib/python3.7/site-packages/tensorflow_core/python/keras/backend.py", line 3476, in call
run_metadata=self.run_metadata)
File "/home/hyj/anaconda3/envs/py37tf15/lib/python3.7/site-packages/tensorflow_core/python/client/session.py", line 1472, in call
run_metadata_ptr)
tensorflow.python.framework.errors_impl.InternalError: 2 root error(s) found.
(0) Internal: Blas GEMM launch failed : a.shape=(3, 512), b.shape=(512, 256), m=3, n=256, k=512
[[{{node bidirectional/forward_lstm_1/while/MatMul}}]]
[[softmax/truediv/_209]]
(1) Internal: Blas GEMM launch failed : a.shape=(3, 512), b.shape=(512, 256), m=3, n=256, k=512
[[{{node bidirectional/forward_lstm_1/while/MatMul}}]]
0 successful operations.
0 derived errors ignored.

---

thank you !

[mvoelk]

layer missing zero_padding2d_5

You can ignore this message. We do not need a extra layer for padding :)

The master branch is up to date for TF 2.x. I'm not sure, 2.0.0-beta1 may be too low. You could try to update to 2.2, what could be painful on Stretch. The tf1 branch should run with TF 1.15 and Keras, not TF-Keras. You can ignore the tf2 branch.

[hongyinjie]

layer missing zero_padding2d_5

You can ignore this message. We do not need a extra layer for padding :)

The master branch is up to date for TF 2.x. I'm not sure, 2.0.0-beta1 may be too low. You could try to update to 2.2, what could be painful on Stretch. The tf1 branch should run with TF 1.15 and Keras, not TF-Keras. You can ignore the tf2 branch.

thank you very much!
I will try it immediately