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Readme.md

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+### Documentation for TensorFlow Implementation of Kolmogorov-Arnold Network (KAN)
+
+#### Introduction
+The provided implementation includes a customizable neural network architecture based on Kolmogorov-Arnold Networks (KANs), 
+utilizing TensorFlow's API. KANs aim to efficiently approximate multivariate functions by employing nonlinear transformations 
+with fewer parameters compared to traditional deep neural networks.
+
+#### Modules and Dependencies
+- **TensorFlow:** Main library providing tools for machine learning and neural network construction.
+
+#### Classes and Functions
+
+##### `KANLinear` Layer
+- **Description:** Custom TensorFlow layer implementing a linear transformation followed by a B-spline transformation as part of a KAN.
+- **Parameters:**
+  - `in_features`: Integer, number of input features.
+  - `out_features`: Integer, number of output features.
+  - `grid_size`: Integer, number of grid points for B-spline basis.
+  - `spline_order`: Integer, order of the spline (degree is `spline_order - 1`).
+  - `activation`: String, activation function to use after summing base and spline outputs.
+  - `regularization_factor`: Float, factor for L2 regularization.
+  - `grid_range`: Tuple, range of the grid used in B-spline transformation.
+- **Methods:**
+  - `build_grid`: Initializes the grid used for B-spline transformations.
+  - `call`: Computes the output of the layer using both linear and spline transformations.
+  - `compute_spline_output`: Calculates the output from the spline transformation.
+
+##### `B_batch_tf` Function
+- **Description:** Computes B-spline basis values for input values using a specified grid and order.
+- **Parameters:**
+  - `x`: TensorFlow Tensor, input values.
+  - `grid`: TensorFlow Tensor, grid points for the splines.
+  - `k`: Integer, order of B-spline.
+  - `extend`: Boolean, whether to extend the grid to handle boundaries.
+- **Returns:** TensorFlow Tensor of B-spline basis values.
+
+##### `extend_grid_tf` Function
+- **Description:** Extends a given grid by a specified number of points on both ends.
+- **Parameters:**
+  - `grid`: TensorFlow Tensor, original grid points.
+  - `k_extend`: Integer, number of points to extend on each side.
+- **Returns:** Extended grid.
+
+##### `KAN` Class
+- **Description:** Sequential model that aggregates multiple `KANLinear` layers to form a complete KAN.
+- **Parameters:**
+  - `layers_configurations`: List of dictionaries, configurations for each `KANLinear` layer.
+
+##### `get_activations` Function
+- **Description:** Utility function to fetch activations from a specified layer in the model.
+- **Parameters:**
+  - `model`: TensorFlow model from which to fetch activations.
+  - `model_inputs`: Input data to the model.
+  - `layer_name`: Optional name of the layer to specifically fetch activations.
+- **Returns:** Activations from the specified layer or all layers if none specified.
+
+#### Notes and Improvements
+1. **Error Handling:** Consider adding error handling for potential issues with input types and values.
+2. **Efficiency:** Analyze and optimize the computation of B-spline basis, which can be critical for performance.
+3. **Documentation:** Ensure each method and function is accompanied by comprehensive docstrings in the code.
+
+### Conclusion
+This documentation provides an overview and detailed explanation of each component in the TensorFlow implementation of KAN. 
+For practical use, ensure proper testing and validation of the functions, especially around the numerical stability of the B-spline calculations.
+
+Feel free to ask if you need clarificattion or found a bug in ISSUE tab!