Python module

functional

Provides experimental functional APIs for tensor operations.

WARNING

This module contains experimental APIs that are subject to change or removal in future versions. Use with caution in production environments.

This module provides functional-style tensor operations that work seamlessly with both MAX Graph construction and eager Tensor execution. All operations are wrapped versions of the core graph operations that automatically handle different execution contexts. These operations can be used in both graph construction and eager execution.

`abs()`

max.experimental.functional.abs(x)

Computes the absolute value element-wise. See max.graph.ops.abs() for details.

Parameters:: x (Value[TensorType] | TensorValue | Shape | Dim | HasTensorValue | int | float | integer[Any] | floating[Any] | DLPackArray)
Return type:: TensorValue

`add()`

max.experimental.functional.add(lhs, rhs)

Adds two tensors element-wise. See max.graph.ops.add() for details.

Parameters:

lhs (Value[TensorType] | TensorValue | Shape | Dim | HasTensorValue | int | float | integer[Any] | floating[Any] | DLPackArray)
rhs (Value[TensorType] | TensorValue | Shape | Dim | HasTensorValue | int | float | integer[Any] | floating[Any] | DLPackArray)

Return type:

WARNING​

abs()​

add()​

argmax()​

argmin()​

argsort()​

as_interleaved_complex()​

atanh()​

avg_pool2d()​

band_part()​

broadcast_to()​

buffer_store()​

buffer_store_slice()​

cast()​

chunk()​

constant()​

constant_external()​

conv2d()​

conv2d_transpose()​

conv3d()​

cos()​

cumsum()​

custom()​

div()​

equal()​

erf()​

exp()​

flatten()​

floor()​

fold()​

functional()​

gather()​

gather_nd()​

gelu()​

greater()​

greater_equal()​

hann_window()​

irfft()​

is_inf()​

is_nan()​

layer_norm()​

log()​

log1p()​

logical_and()​

logical_not()​

logical_or()​

logical_xor()​

logsoftmax()​

masked_scatter()​

matmul()​

max()​

max_pool2d()​

mean()​

min()​

mod()​

mul()​

negate()​

nonzero()​

not_equal()​

outer()​

pad()​

permute()​

pow()​

range()​

relu()​

repeat_interleave()​

reshape()​

round()​

rsqrt()​

scatter()​

scatter_nd()​

sigmoid()​

silu()​

sin()​

slice_tensor()​

softmax()​

split()​

sqrt()​

squeeze()​

stack()​

WARNING

`abs()`

`add()`

`argmax()`

`argmin()`

`argsort()`

`as_interleaved_complex()`

`atanh()`

`avg_pool2d()`

`band_part()`

`broadcast_to()`

`buffer_store()`

`buffer_store_slice()`

`cast()`

`chunk()`

`constant()`

`constant_external()`

`conv2d()`

`conv2d_transpose()`

`conv3d()`

`cos()`

`cumsum()`

`custom()`

`div()`

`equal()`

`erf()`

`exp()`

`flatten()`

`floor()`

`fold()`

`functional()`

`gather()`

`gather_nd()`

`gelu()`

`greater()`

`greater_equal()`

`hann_window()`

`irfft()`

`is_inf()`

`is_nan()`

`layer_norm()`

`log()`

`log1p()`

`logical_and()`

`logical_not()`

`logical_or()`

`logical_xor()`

`logsoftmax()`

`masked_scatter()`

`matmul()`

`max()`

`max_pool2d()`

`mean()`

`min()`

`mod()`

`mul()`

`negate()`

`nonzero()`

`not_equal()`

`outer()`

`pad()`

`permute()`

`pow()`

`range()`

`relu()`

`repeat_interleave()`

`reshape()`

`round()`

`rsqrt()`

`scatter()`

`scatter_nd()`

`sigmoid()`

`silu()`

`sin()`

`slice_tensor()`

`softmax()`

`split()`

`sqrt()`

`squeeze()`

`stack()`