Baddbmm

Performs a batch matrix-matrix product of matrices in batch1 and batch2. input is added to final result.

Abstract Signature:

Baddbmm(input: Tensor, batch1: Tensor, batch2: Tensor, beta: float = 1.0, alpha: float = 1.0)

PyTorchJAX (Core)NumPyKerasApple MLXFlax NNX

PyTorch

API: torch.baddbmm

Strategy: Direct Mapping

Official Docs ↗

JAX (Core)

API: —

Strategy: Macro '{beta} * {input} + {alpha} * jax.numpy.matmul({batch1}, {batch2})'

NumPy

API: —

Strategy: Macro '{beta} * {input} + {alpha} * numpy.matmul({batch1}, {batch2})'

Keras

API: —

Strategy: Macro '{beta} * {input} + {alpha} * keras.ops.matmul({batch1}, {batch2})'

Apple MLX

API: —

Strategy: Macro '{beta} * {input} + {alpha} * mlx.core.matmul({batch1}, {batch2})'

Flax NNX

API: —

Strategy: Macro '{beta} * {input} + {alpha} * jax.numpy.matmul({batch1}, {batch2})'