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@apbose apbose commented Aug 14, 2024

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@apbose apbose requested a review from peri044 August 14, 2024 06:16
@github-actions github-actions bot added component: tests Issues re: Tests component: conversion Issues re: Conversion stage component: converters Issues re: Specific op converters component: api [Python] Issues re: Python API component: dynamo Issues relating to the `torch.compile` or `torch._dynamo.export` paths labels Aug 14, 2024
@github-actions github-actions bot requested a review from gs-olive August 14, 2024 06:16
shapes = [i * j for i, j in zip(input.shape, dims)]
layer = ctx.net.add_slice(input, tuple(starts), tuple(shapes), tuple(strides))
else:
shapes = None
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should shapes be a list here ?

input, start=trt.Dims(), shape=trt.Dims(), stride=trt.Dims()
)
layer.set_input(1, tuple(starts))
layer.set_input(2, tuple(shapes))
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Looks like we are setting a list of ITensors as a second input. But shouldn't the second input be an ITensor (which is the concatenated output of these shapes ) ? or both of them work ?

((2,), (3,), (6,), (2, 2)),
((2,), (3,), (6,), (0, 2)),
# 2d cases
((3, 1), (3, 1), (6, 1), (0,)),
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is tiling with dims = (0,) same as tiling with (1,) ?

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Tiling with dims = (0,) results in that particular dimension as 0 in the tiled tensor. In the above case though it prepends -1 resulting in dims being (-1, 0) post which the dynamic input tensor is tiled

@apbose apbose requested a review from peri044 August 27, 2024 15:44
@peri044 peri044 merged commit ffa4f64 into main Aug 29, 2024
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cla signed component: api [Python] Issues re: Python API component: conversion Issues re: Conversion stage component: converters Issues re: Specific op converters component: dynamo Issues relating to the `torch.compile` or `torch._dynamo.export` paths component: tests Issues re: Tests

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3 participants