ttnn.experimental.conv3d

ttnn.experimental.conv3d = Operation(python_fully_qualified_name='ttnn.experimental.conv3d', function=<ttnn._ttnn.operations.experimental.conv3d_t object>, preprocess_golden_function_inputs=<function default_preprocess_golden_function_inputs>, golden_function=None, postprocess_golden_function_outputs=<function default_postprocess_golden_function_outputs>, is_cpp_operation=True, is_experimental=False)

Applies a 3D convolution over an input signal composed of several input planes. Expects Input Tensor in [N, D, H, W, C] format. Expects Weight Tensor in [1, 1, kD * kH * kW * C_in, C_out] format. Expects Bias Tensor in [1, 1, 1, 32, C_out] format. Input must be in row major interleaved format. Output will be in row major interleaved format.

Parameters:

  • input_tensor (ttnn.Tensor) – Input tensor.

  • weight_tensor (ttnn.Tensor) – Weight tensor.

  • bias_tensor (ttnn.Tensor) – Bias tensor.

  • config (ttnn.Conv3dConfig) – Configuration for the Conv3D operation.

  • memory_config (ttnn.MemoryConfig) – Memory configuration for the output of the Conv3D operation.

  • compute_kernel_config (ttnn.DeviceComputeKernelConfig) – Compute kernel configuration for the Conv3D operation.

  • queue_id – Queue ID for the Conv3D operation.

Returns:

Output tensor after applying the Conv3D operation.

Return type:

ttnn.Tensor