code review fixes

model_compression_toolkit/core/common/quantization/quantization_params_generation/error_functions.py

@@ -150,21 +150,20 @@ def _kl_error_function_wrapper(x: np.ndarray,
                                n_bins: int = 2048,
                                n_bits: int = 8) -> np.ndarray:
     """
-    Compute the error function between a tensor to its quantized version per channel.
-    The error is computed based on the KL-divergence the distributions have.
-    Number of bins to use when computing the histogram of the float tensor is passed.
-    The threshold and number of bits that were used to quantize the tensor are needed to compute the
-    histograms boundaries and the number of quantized bins.
+    Computes the error function between a tensor and its quantized version for each channel.
+    The error is based on the KL-divergence between the distributions.
+    The function uses a specified number of bins to compute the histogram of the float tensor.
+    It requires the threshold and number of bits used for quantization to determine the histogram's boundaries and the number of quantized bins.
 
     Args:
         x: Float tensor.
-        range_min: array of min bound on the quantization range.
-        range_max: array of max bound on the quantization range.
+        range_min: Array specifying the minimum bound of the quantization range for each channel.
+        range_max: Array specifying the maximum bound of the quantization range for each channel.
         n_bins: Number of bins for the float histogram.
-        n_bits: Number of bits the quantized tensor was quantized by.
+        n_bits: Number of bits used for quantization.
 
     Returns:
-        The KL-divergence of the float histogram and the quantized histogram of the tensors, per channel
+        An array containing the KL-divergence between the float and quantized histograms of the tensor for each channel.
 
     """
 
@@ -378,13 +377,13 @@ def get_threshold_selection_tensor_error_function(quantization_method: Quantizat
     Returns the error function compatible to the provided threshold method,
     to be used in the threshold optimization search for tensor quantization.
     Args:
-        quantization_method: Quantization method for threshold selection
-        quant_error_method: the requested error function type.
-        p: p-norm to use for the Lp-norm distance.
-        axis: Axis along which the operator has been computed.
-        norm: whether to normalize the error function result.
-        n_bits: Number of bits to quantize the tensor.
-        signed: signed input
+        quantization_method: Method used for selecting the quantization threshold.
+        quant_error_method: Type of error function requested.
+        p: P-norm to use for calculating the Lp-norm distance.
+        axis: Axis along which the operation has been performed.
+        norm: Indicates whether to normalize the result of the error function.
+        n_bits: Number of bits used to quantize the tensor.
+        signed: Indicates whether the input is signed.
 
     Returns: a Callable method that calculates the error between a tensor and a quantized tensor.
     """

model_compression_toolkit/core/common/quantization/quantization_params_generation/qparams_search.py

@@ -726,7 +726,7 @@ def _error_function_wrapper(error_function: Callable,
         q_tensor: Numpy array with quantized tensor's content.
         in_params: Quantization params the tensor is quantized by (used in specific error functions only).
 
-    Returns: A array of error values per-channel for the quantized tensor, according to the error function.
+    Returns: An array of error values for each channel of the quantized tensor, as determined by the specified error function.
     """
     return error_function(float_tensor, q_tensor, in_params)