Update packages for macOS

[DocGarbanzo]

Unfreeze matplotlib and add tensorflow-metal to macos install for apple silicon

[cfox570]

I tried the install (main branch with your updated files). The install works but training is strange. Here is a fragment from the last Epoch: Note the loss is astronomical. MacBook Air M1. Are you getting valid results?

178/178 [==============================] - ETA: 0s - loss: 119965049405247305285632.0000 - n_outputs0_loss: 80119361630094294515712.0000 - n_outputs1_loss: 39845651746355991805952.0000 
Epoch 6: val_loss did not improve from 107208061654925312.00000
178/178 [==============================] - 21s 117ms/step - loss: 119965049405247305285632.0000 - n_outputs0_loss: 80119361630094294515712.0000 - n_outputs1_loss: 39845651746355991805952.0000 - val_loss: 134251115941612859949056.0000 - val_n_outputs0_loss: 15944611674736914595840.0000 - val_n_outputs1_loss: 118306526784874082205696.0000
INFO:donkeycar.parts.keras:////////// Finished training in: 0:02:25.759302 //////////

I then uninstalled tensorflow-metal and though it was slow I got expected results:

Epoch 76: val_loss did not improve from 0.04335
178/178 [==============================] - 50s 282ms/step - loss: 0.0500 - n_outputs0_loss: 0.0365 - n_outputs1_loss: 0.0135 - val_loss: 0.0438 - val_n_outputs0_loss: 0.0316 - val_n_outputs1_loss: 0.0122
Epoch 77/100
178/178 [==============================] - ETA: 0s - loss: 0.0483 - n_outputs0_loss: 0.0350 - n_outputs1_loss: 0.0133  
Epoch 77: val_loss did not improve from 0.04335
178/178 [==============================] - 75s 420ms/step - loss: 0.0483 - n_outputs0_loss: 0.0350 - n_outputs1_loss: 0.0133 - val_loss: 0.0446 - val_n_outputs0_loss: 0.0323 - val_n_outputs1_loss: 0.0123
INFO:donkeycar.parts.keras:////////// Finished training in: 1:24:04.925587 //////////

I have been trying to get this to work since version 5.0 +. The version running Tensorflow 2.9 with the appropriate Python 3.9 and Tensorflow-metal 0.5.0 works. I have read that others have problems with the newer versions. And no updates from Apple since last year September.

[DocGarbanzo]

I tried the install (main branch with your updated files). The install works but training is strange. Here is a fragment from the last Epoch: Note the loss is astronomical. MacBook Air M1. Are you getting valid results?

178/178 [==============================] - ETA: 0s - loss: 119965049405247305285632.0000 - n_outputs0_loss: 80119361630094294515712.0000 - n_outputs1_loss: 39845651746355991805952.0000 
Epoch 6: val_loss did not improve from 107208061654925312.00000
178/178 [==============================] - 21s 117ms/step - loss: 119965049405247305285632.0000 - n_outputs0_loss: 80119361630094294515712.0000 - n_outputs1_loss: 39845651746355991805952.0000 - val_loss: 134251115941612859949056.0000 - val_n_outputs0_loss: 15944611674736914595840.0000 - val_n_outputs1_loss: 118306526784874082205696.0000
INFO:donkeycar.parts.keras:////////// Finished training in: 0:02:25.759302 //////////

I then uninstalled tensorflow-metal and though it was slow I got expected results:

Epoch 76: val_loss did not improve from 0.04335
178/178 [==============================] - 50s 282ms/step - loss: 0.0500 - n_outputs0_loss: 0.0365 - n_outputs1_loss: 0.0135 - val_loss: 0.0438 - val_n_outputs0_loss: 0.0316 - val_n_outputs1_loss: 0.0122
Epoch 77/100
178/178 [==============================] - ETA: 0s - loss: 0.0483 - n_outputs0_loss: 0.0350 - n_outputs1_loss: 0.0133  
Epoch 77: val_loss did not improve from 0.04335
178/178 [==============================] - 75s 420ms/step - loss: 0.0483 - n_outputs0_loss: 0.0350 - n_outputs1_loss: 0.0133 - val_loss: 0.0446 - val_n_outputs0_loss: 0.0323 - val_n_outputs1_loss: 0.0123
INFO:donkeycar.parts.keras:////////// Finished training in: 1:24:04.925587 //////////

I have been trying to get this to work since version 5.0 +. The version running Tensorflow 2.9 with the appropriate Python 3.9 and Tensorflow-metal 0.5.0 works. I have read that others have problems with the newer versions. And no updates from Apple since last year September.

Thanks @cfox570 for helping to test the code. Training for me works without any problems on my MB Pro M3. Can you please check which versions of tensorflow, tensorflow-metal and python are getting installed in your environment? I am seeing the following:

tensorflow                   2.15.1
tensorflow-metal             1.1.0
python                       3.11.9 

Note, when you check out the version of the PR you should be seeing the version v5.2.dev3 if you are loading donkeycar. Also, do you maybe train using a transfer model? I could imagine that the formats of the saved models might differ when using tensorflow-metal and you might need to start from scratch.

[cfox570]

tensorflow 2.15.1 tensorfzlow-estimator 2.15.0 tensorflow-metal 1.1.0 python 3.11.11 Note I tried many other Python versions in the past summer. Conda 24.9.2 We obviously have different data. Are you using donkeycar or simulation data? Craig On Dec 28, 2024, at 2:41 PM, DocGarbanzo ***@***.***> wrote: tensorflow 2.15.1 tensorflow-metal 1.1.0 python 3.11.9

[DocGarbanzo]

I am using Ed's circuit launch data from the donkeycar_dataset repo.

[cfox570]

Can you send me the link? On Jan 15, 2025, at 3:23 AM, DocGarbanzo ***@***.***> wrote: I am using Ed's circuit launch data from the donkeycar_dataset repo. — Reply to this email directly, view it on GitHub <#1203 (comment)>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AADERR7DHQARCNBUP27U2JD2KYLINAVCNFSM6AAAAABTTX6KOWVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDKOJRHEYTMMBUGI>. You are receiving this because you were mentioned.