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Open deep learning compiler stack for cpu, gpu and specialized accelerators

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This PR fixes the shuffle rewrite pass to handle the case where the vector lanes are larger than the data type of the input vector.

This allows existing files to be updated. cc @tqchen

This commit introduces rewrite rules for indices which can arise from splitting axes by scalable factors (e.g. `xo, xi = sch.split(x, factors = [None, 8 * T.vscale()])`): ``` (v_x_o *...

I would like to ask what configuration causes the generated file types to be different? ![捕获](https://github.com/apache/tvm/assets/122245479/a66ee8e1-30be-4449-b66d-6157345c4d8c)

type: bug
needs-triage

This PR fixes a bug in the PagedKVCache which may happen when the sequence removal order is not consistent with the reverse order of sequence add/fork order. With this fix,...

How should the following issues be resolved when running demo_static? demo_static.c: In function ‘main’: demo_static.c:52:3: warning: ignoring return value of ‘fread’, declared with attribute warn_unused_result [-Wunused-result] (void)fread(input_storage, 3 * 224...

type: bug
needs-triage

How should the following issues be resolved when running demo_static? demo_static.c: In function ‘main’: demo_static.c:52:3: warning: ignoring return value of ‘fread’, declared with attribute warn_unused_result [-Wunused-result] (void)fread(input_storage, 3 * 224...

type: bug
needs-triage

How should the following issues be resolved when running demo_static? demo_static.c: In function ‘main’: demo_static.c:52:3: warning: ignoring return value of ‘fread’, declared with attribute warn_unused_result [-Wunused-result] (void)fread(input_storage, 3 * 224...

type: bug
needs-triage

### Actual behavior ![image](https://github.com/apache/tvm/assets/29506758/e9782c35-ee51-4783-8528-5315e211f814) What actually happened ### Environment Any environment details, such as: Operating System, TVM version, etc ### Steps to reproduce ``` import tvm import tvm.relay as relay...

type: bug
needs-triage

This commit extends the SME conv2d NHWC schedule to support convolutions with float16 inputs (data and kernel) and a float32 output using the tensor intrinsics added in #16981. cc @ekalda...