Cerebras Basics
Getting Started with Cerebras Wafer-Scale Cluster
Getting Started with Original Cerebras Installation
Scripts and Templates (Original Cerebras Installation Only)
run.py
csrun_cpu
csrun_wse
Model Zoo Repository
Cerebras Advanced
Develop with TensorFlow (Pipelined Mode Only)
Develop with PyTorch (Pipelined Mode Only)
Compiler Reports (Pipelined Mode Only)
Extensions (Original Cerebras Installation Only)
Bases: modelzoo.common.tf.layers.BaseLayer.BaseLayer
modelzoo.common.tf.layers.BaseLayer.BaseLayer
Dense layer that takes in a kernel as a shared weight. Can also optionally add a bias.
Apply the densely-connected layer.
inputs (Tensor) – An N-D tensor with the shape: (batch_size, ..., input_dim).
(batch_size, ..., input_dim)
kernel (Tensor) – A 2-D tensor with the shape: (units, input_dim). The dense kernel.
(units, input_dim)
transpose_kernel (bool) – Whether to transpose the kernel when performing tf.matmul(inputs, kernel).
tf.matmul(inputs, kernel)
An N-D tensor with shape: (batch_size, ..., units).
(batch_size, ..., units)
Tensor
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tf.layers.SegmentEmbeddingLayer module
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tf.layers.SoftmaxLayer module