Modularize cumsum.

[annxingyuan]

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This change is 

[tafsiri]

Looks great!

Reviewed 14 of 14 files at r1.
Reviewable status: complete! 1 of 1 approvals obtained (waiting on @annxingyuan, @lina128, and @tafsiri)

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tfjs-core/src/ops/cumsum.ts, line 59 at r1 (raw file):

  const forward: ForwardFunc<Tensor> =
      (backend: KernelBackend, save: GradSaveFunc) => {
        axis = axis | 0;

nit: is this needed given the default argument?

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tfjs-core/src/ops/image_ops_test.ts, line 178 at r1 (raw file):

    it('works with other operators, div', async () => {
      // This test ensures that asynchronous backends work with NMS, which

nit (optional) thanks for adding this. I was thinking about and wondering if there is just a better name for this test. If you can think of one feel free to add it. It seems really be about where the data for the inputs resides than other operators per-se

[annxingyuan]

Reviewable status: complete! 1 of 1 approvals obtained (waiting on @lina128)

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tfjs-core/src/ops/cumsum.ts, line 59 at r1 (raw file):

Previously, tafsiri (Yannick Assogba) wrote…

nit: is this needed given the default argument?

Done

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tfjs-core/src/ops/image_ops_test.ts, line 178 at r1 (raw file):

Previously, tafsiri (Yannick Assogba) wrote…

nit (optional) thanks for adding this. I was thinking about and wondering if there is just a better name for this test. If you can think of one feel free to add it. It seems really be about where the data for the inputs resides than other operators per-se

Done

[lina128]

Reviewable status: complete! 2 of 1 approvals obtained (waiting on @annxingyuan and @lina128)

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tfjs-core/src/gradients/Cumsum_grad.ts, line 29 at r2 (raw file):

    const [x] = saved;
    const cumsumAttrs: CumsumAttrs = attrs as {} as CumsumAttrs;
    const {axis, exclusive, reverse} = cumsumAttrs;

nit: Can be one line: {axis, exclusive, reverse} = attrs as {} as CumsumAttrs;

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tfjs-core/src/gradients/Cumsum_grad.ts, line 35 at r2 (raw file):

        const permutation = getAxesPermutation([axis], x.rank);

        let out = dy.cumsum(axis, exclusive, !reverse);

remove chained op.

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tfjs-core/src/gradients/Cumsum_grad.ts, line 38 at r2 (raw file):

        if (permutation != null) {
          out = out.transpose(permutation);

remove chained op.

[annxingyuan]

Reviewable status: complete! 2 of 1 approvals obtained (waiting on @lina128)

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tfjs-core/src/gradients/Cumsum_grad.ts, line 29 at r2 (raw file):

Previously, lina128 (Na Li) wrote…

nit: Can be one line: {axis, exclusive, reverse} = attrs as {} as CumsumAttrs;

Done

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tfjs-core/src/gradients/Cumsum_grad.ts, line 35 at r2 (raw file):

Previously, lina128 (Na Li) wrote…

remove chained op.

Done

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tfjs-core/src/gradients/Cumsum_grad.ts, line 38 at r2 (raw file):

Previously, lina128 (Na Li) wrote…

remove chained op.

Done