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The output shape of the tf.conv1d operation on the CPU backend is inconsistent with the output shape on the TensorFlow backend #8404

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liliquan0118 opened this issue Oct 3, 2024 · 0 comments

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@liliquan0118
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Please make sure that this is a bug. As per our
GitHub Policy,
we only address code/doc bugs, performance issues, feature requests and
build/installation issues on GitHub. tag:bug_template

System information

  • Have I written custom code (as opposed to using a stock example script provided in TensorFlow.js):
  • OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Ubuntu 20.04, Macos 13.3 (22E252)
  • Mobile device (e.g. iPhone 8, Pixel 2, Samsung Galaxy) if the issue happens on mobile device:
  • TensorFlow.js installed from (npm or script link): script link
  • TensorFlow.js version (use command below): 4.2.0
  • Browser version: Chrome Version 128.0.6613.86 (Official Build) (arm64)
  • Tensorflow.js Converter Version:

Describe the current behavior

    var x = [[1165770376.0615559],[2071486936.2386856],[1151127540.6558466]]
    var filter = [[[1154931189.8559952]],[[961048433.571806]]]
    var stride = 2
    var pad = 0
    var dataFormat = "NWC"
    var dilation = 1
    var dimRoundingMode = "ceil"
    var result = tf.conv1d(x, filter,stride,pad,dataFormat,dilation,dimRoundingMode);
    console.log("the result of ", tf.getBackend(), "is:\n" );
    result.print();

The shape of the result is inconsistent when executing the above code snippets on CPU and tensorflow backends.

Output:
image

Describe the expected behavior
The output should be consistent across all backends.

Standalone code to reproduce the issue
Provide a reproducible test case that is the bare minimum necessary to generate
the problem. If possible, please share a link to Colab/CodePen/any notebook.

var tf=require("@tensorflow/tfjs");
require("@tensorflow/tfjs-node");

async function conv1d(backend){
    await tf.setBackend(backend);
    await tf.ready() 
    var x = [[1165770376.0615559],[2071486936.2386856],[1151127540.6558466]]
    var filter = [[[1154931189.8559952]],[[961048433.571806]]]
    var stride = 2
    var pad = 0
    var dataFormat = "NWC"
    var dilation = 1
    var dimRoundingMode = "ceil"
    var result = await tf.conv1d(x, filter,stride,pad,dataFormat,dilation,dimRoundingMode);
    await console.log("the result of ", tf.getBackend(), "is:\n" );
    await result.print();
}
async function test() {
    await conv1d("cpu");
    // await conv1d("webgl");
    await conv1d("tensorflow");
}

test();

Other info / logs Include any logs or source code that would be helpful to
diagnose the problem. If including tracebacks, please include the full
traceback. Large logs and files should be attached.

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