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vadiklyutiy
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Dec 19, 2024
The issue is caused by a wrong layout for the bias tensor. For example, we consider a bias tensor of shape (64, ) and its layout can be written as `(64, ): (1, )` However, we can expand the layout by adding axes with 1-shape. For example, `(64, 1):(1, 1)` Since the shape is equal to 1, the stride can be any number. The stride corresponding to the 1-shape actually doesn't affect the computation of the address. But two strides that are equal to one will influence the instruction selection, and the invalid memory instruction leads to the misaligned access. To fix this issue, we force the stride paired with 1-shape to be 0. The layout is equivalent when computing the memory address, and this will help the compiler make the right decision in the instruction selection pass. closes #404 Co-authored-by: xiaocenxiaocen <xiao.zhang@centml.ai>
vadiklyutiy
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Dec 20, 2024
The issue is caused by a wrong layout for the bias tensor. For example, we consider a bias tensor of shape (64, ) and its layout can be written as `(64, ): (1, )` However, we can expand the layout by adding axes with 1-shape. For example, `(64, 1):(1, 1)` Since the shape is equal to 1, the stride can be any number. The stride corresponding to the 1-shape actually doesn't affect the computation of the address. But two strides that are equal to one will influence the instruction selection, and the invalid memory instruction leads to the misaligned access. To fix this issue, we force the stride paired with 1-shape to be 0. The layout is equivalent when computing the memory address, and this will help the compiler make the right decision in the instruction selection pass. closes #404 Co-authored-by: xiaocenxiaocen <xiao.zhang@centml.ai>
vadiklyutiy
pushed a commit
that referenced
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Dec 26, 2024
The issue is caused by a wrong layout for the bias tensor. For example, we consider a bias tensor of shape (64, ) and its layout can be written as `(64, ): (1, )` However, we can expand the layout by adding axes with 1-shape. For example, `(64, 1):(1, 1)` Since the shape is equal to 1, the stride can be any number. The stride corresponding to the 1-shape actually doesn't affect the computation of the address. But two strides that are equal to one will influence the instruction selection, and the invalid memory instruction leads to the misaligned access. To fix this issue, we force the stride paired with 1-shape to be 0. The layout is equivalent when computing the memory address, and this will help the compiler make the right decision in the instruction selection pass. closes #404 Co-authored-by: xiaocenxiaocen <xiao.zhang@centml.ai>
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