semvec/pypi-packages huggingface dataset:
loglu-tensorflow 0.0.1
LogLU Activation Function - TensorFlow
License: Apache-2.0
Requires Python: >=3.6


### Installation

To use LogLU, simply install it using the following command:

```bash
pip install loglu-tensorflow
```

### Implementation

```python
import tensorflow as tf
from loglu_tensorflow import LogLU # Importing the LogLU activation function from the loglu package

# Define a model
model = tf.keras.models.Sequential([
    tf.keras.layers.Dense(128, input_shape=(784,)),
    tf.keras.layers.Activation(LogLU()),  # Use LogLU as the activation function
    tf.keras.layers.Dense(10, activation='softmax')
])

# Compile the model

# Summary of the model
model.summary()
```

## License

LogLU-TensorFlow is released under the [Apache License 2.0](https://github.com/XenReZ/LogLU-TensorFlow/blob/main/LICENSE).
zengrad-pytorch 0.0.1
ZenGrad Optimizer - Pytorch
License: Apache-2.0
Requires Python: >=3.6


## Installation

To install ZenGrad, run the following command:

```bash
pip install zengrad-pytorch
```

## Implementation

```python
import torch
from zengrad_pytorch import ZenGrad  # Custom optimizer

# Define the model

# Instantiate the model
model = SimpleModel()

# Define loss function
criterion = nn.CrossEntropyLoss()

# Instantiate optimizer
optimizer = ZenGrad(model.parameters(), lr=0.01, weight_decay=1e-4, epsilon=1e-8) # <---- In This Way

# Model summary (optional)
print(model)

```

## License

ZenGrad_pytorch is released under the [Apache License 2.0](https://github.com/XenReZ/ZenGrad-PyTorch/blob/main/LICENSE).