Patch pydantic release (#99)

* fix

* fix

* patch pydantic release

* update requirements.txt

* update reproducibility examples

* update configs

examples/scripts/configs/cifar10/base_training_config.json

@@ -1,7 +1,8 @@
 {
  "name": "BaseTrainerConfig",
  "output_dir": "my_models_on_cifar",
- "batch_size": 100,
+ "per_device_train_batch_size": 100,
+ "per_device_eval_batch_size": 100,
  "num_epochs": 100,
  "learning_rate": 1e-4,
  "steps_saving": null,

examples/scripts/configs/dsprites/beta_tc_vae/base_training_config.json

@@ -1,7 +1,8 @@
 {
  "name": "BaseTrainerConfig",
  "output_dir": "reproducibility/dsprites",
- "batch_size": 1000,
+ "per_device_train_batch_size": 1000,
+ "per_device_eval_batch_size": 1000,
  "num_epochs": 50,
  "learning_rate": 1e-3,
  "steps_saving": null,

examples/scripts/configs/dsprites/factorvae/base_training_config.json

@@ -1,7 +1,8 @@
 {
  "name": "BaseTrainerConfig",
  "output_dir": "reproducibility/dsprites",
- "batch_size": 64,
+ "per_device_train_batch_size": 64,
+ "per_device_eval_batch_size": 64,
  "num_epochs": 500,
  "learning_rate": 1e-3,
  "steps_saving": 50,

examples/scripts/configs/mnist/base_training_config.json

@@ -1,7 +1,8 @@
 {
  "name": "BaseTrainerConfig",
  "output_dir": "my_models_on_mnist",
- "batch_size": 100,
+ "per_device_train_batch_size": 100,
+ "per_device_eval_batch_size": 100,
  "num_epochs": 100,
  "learning_rate": 1e-3,
  "steps_saving": null,

requirements.txt

@@ -1,7 +1,7 @@
 cloudpickle>=2.1.0
 imageio
 numpy>=1.19
-pydantic>=1.8.2
+pydantic==1.8.2
 scikit-learn
 scipy>=1.7.1
 torch>=1.10.1

setup.py

@@ -29,7 +29,7 @@
  "cloudpickle>=2.1.0",
  "imageio",
  "numpy>=1.19",
- "pydantic>=1.8.2",
+ "pydantic==1.8.2",
  "scikit-learn",
  "scipy>=1.7.1",
  "torch>=1.10.1",