dataframe-hasktorch 0.1.0.1 → 0.1.0.2

raw patch · 3 files changed

+9/−5 lines, 3 files

Files

• CHANGELOG.md +4/−0
• dataframe-hasktorch.cabal +4/−4
• src/DataFrame/Hasktorch.hs +1/−1

@@ -1,5 +1,9 @@ # Revision history for dataframe-hasktorch +## 0.1.0.2++* Add unbox constraint to `flattenFeatures`.+ ## 0.1.0.1  * Export `toIntTensor` function that converts a dataframe to an Int tensor.

@@ -1,19 +1,19 @@ cabal-version:      3.0 name:               dataframe-hasktorch-version:            0.1.0.1+version:            0.1.0.2 synopsis:           Converts between dataframes and hasktorch tensors  description:             This package provides seamless conversion between dataframes and hasktorch tensors,     bridging the gap between data manipulation and machine learning workflows.-    .+     Key features:-    .+     * Convert dataframes to floating-point or integer tensors for ML training     * Automatic handling of multi-column and single-column dataframes     * Smart dimensional handling (1D tensors for single columns, 2D for multiple)     * Type-safe conversions with comprehensive error handling-    .+     Typical workflow: load and transform data using dataframes, then convert to     tensors for training neural networks with hasktorch. 

@@ -105,7 +105,7 @@          in             reshape dims' (asTensor (flattenFeatures m)) -flattenFeatures :: V.Vector (VU.Vector a) -> VU.Vector a+flattenFeatures :: (VU.Unbox a) => V.Vector (VU.Vector a) -> VU.Vector a flattenFeatures rows =     let         total = V.foldl' (\s v -> s + VU.length v) 0 rows