Addbmm

Performs batch matrix-matrix product of matrices with reduced add step.

Abstract Signature:

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

PyTorchJAX (Core)NumPyKerasTensorFlowApple MLXFlax NNX

PyTorch

API: torch.addbmm

Strategy: Direct Mapping

Official Docs ↗

JAX (Core)

API: jax.numpy.sum

Strategy: Macro '{beta} * {input} + {alpha} * jax.numpy.sum(jax.numpy.matmul({batch1}, {batch2}), axis=0)'

NumPy

API: numpy.matmul

Strategy: Macro '{beta} * {input} + {alpha} * numpy.sum(numpy.matmul({batch1}, {batch2}), axis=0)'

Keras

API: keras.ops.sum

Strategy: Macro '{beta} * {input} + {alpha} * keras.ops.sum(keras.ops.matmul({batch1}, {batch2}), axis=0)'

TensorFlow

API: tf.linalg.matmul

Strategy: Macro '{beta} * {input} + {alpha} * tf.reduce_sum(tf.linalg.matmul({batch1}, {batch2}), axis=0)'

Apple MLX

API: mlx.core.matmul

Strategy: Macro '{beta} * {input} + {alpha} * mlx.core.sum(mlx.core.matmul({batch1}, {batch2}), axis=0)'

Flax NNX

API: jax.numpy.sum

Strategy: Macro '{beta} * {input} + {alpha} * jax.numpy.sum(jax.numpy.matmul({batch1}, {batch2}), axis=0)'