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Builtin Reference
    • adamupdate
    • analyzeNetwork
    • bilstmLayer
    • classificationLayer
    • combvec
    • convolution1dLayer
    • crossentropy
    • dlarray
    • dlfeval
    • dlgradient
    • dlnetwork
    • dlupdate
    • eluLayer
    • exportONNXNetwork
    • featureInputLayer
    • forward
    • fullyConnectedLayer
    • globalAveragePooling1dLayer
    • layerGraph
    • layerNormalizationLayer
    • lstmLayer
    • padsequences
    • regressionLayer
    • reluLayer
    • sequenceInputLayer
    • softmaxLayer
    • trainingOptions
    • trainnet
    • trainNetwork

dlarray — Create a dlarray compatibility object around host or gpuArray data.

dlarray(X) wraps host or provider-resident gpuArray data and optional dimension labels in a RunMat compatibility object.

Syntax

X = dlarray(data)
X = dlarray(data, fmt)

How dlarray works

  • The underlying Data value is preserved without conversion, including provider-resident gpuArray handles.
  • A second text argument is stored as Format and Labels.
  • Additional constructor options are rejected with explicit compatibility errors.
  • Inside dlfeval, host dlarray values become traced leaves for the bounded dlgradient tape. Supported arithmetic preserves the wrapper and dimension-label metadata.

GPU memory and residency

dlarray preserves provider-resident gpuArray data as wrapper metadata outside autodiff. GPU-backed dlarray tracing is rejected with an explicit provider-gap error until Deep Learning tape kernels are available in the acceleration provider.

Example

Wrap Data

X = dlarray(rand(3,4), 'CB')

Expected output:

dlarray compatibility object.

Using dlarray with coding agents

Open a RunMat example with live inputs, then ask the agent to explain how dlarray changes the result.

Run a small dlarray example, explain the result, then change one input and compare the output.

Related Deep Learning functions

adamupdate · analyzeNetwork · bilstmLayer · classificationLayer · combvec · convolution1dLayer · crossentropy · dlfeval · dlgradient · dlnetwork · dlupdate · eluLayer · exportONNXNetwork · featureInputLayer · forward · fullyConnectedLayer · globalAveragePooling1dLayer · layerGraph · layerNormalizationLayer · lstmLayer · padsequences · regressionLayer · reluLayer · sequenceInputLayer · softmaxLayer · trainingOptions · trainnet · trainNetwork

About RunMat

RunMat is an open-source runtime that executes MATLAB-syntax code blazing on any GPU. It is licensed under the Apache 2.0 license.

  • RunMat automatically optimizes your math for GPU execution on Apple, Nvidia, and AMD hardware. No code changes needed. Simulations that took hours now take minutes.
  • Start running code in seconds. RunMat runs in the browser, on the desktop, or from the CLI. No license server, no IT ticket.

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On this page
  • Syntax
  • How dlarray works
  • GPU memory and residency
  • Example
  • Wrap Data
  • Using dlarray with coding agents
  • Related Deep Learning functions
  • About RunMat