MeanSquaredLogarithmicError

Computes the mean squared logarithmic error between y_true & y_pred.

Abstract Signature:

MeanSquaredLogarithmicError(y_true: Tensor, y_pred: Tensor)

PyTorchJAX (Core)KerasTensorFlowFlax NNXPaxML / Praxis

PyTorch

API: —

Strategy: Macro 'torch.nn.functional.mse_loss(torch.log1p({y_true}), torch.log1p({y_pred}), reduction='none')'

JAX (Core)

API: —

Strategy: Macro 'optax.squared_error(jax.numpy.log1p({y_true}), jax.numpy.log1p({y_pred}))'

Keras

API: keras.losses.mean_squared_logarithmic_error

Strategy: Direct Mapping

Official Docs ↗

TensorFlow

API: tf.keras.losses.mean_squared_logarithmic_error

Strategy: Direct Mapping

Official Docs ↗

Flax NNX

API: —

Strategy: Macro 'optax.squared_error(jax.numpy.log1p({y_true}), jax.numpy.log1p({y_pred}))'

PaxML / Praxis

API: —

Strategy: Macro 'optax.squared_error(jax.numpy.log1p({y_true}), jax.numpy.log1p({y_pred}))'