Slightly improve error message from repeat_interleave kernel (pytorch#157996)

Summary:
In many investigations relating to invalid feature values, the three-argument form of `repeat_interleave` currently prints the following message if there is an inconsistency between `sum(repeats)` and `output_size`:
```
Assertion `result_size == cumsum_ptr[size - 1]` failed.
```

This is a bit hard for model authors to understand so I made the error slightly more comprehensible. After the fix the stdout contains the actual values of these parameters: https://fburl.com/mlhub/cfyyhh3q

```
Invalid input! In `repeat_interleave`, the `output_size` argument (949487) must be the same as the sum of the elements in the `repeats` tensor (949687).
```

In many cases, this is potentially useful information since we know for example that the difference between the two values above (949687-949487=200) happens to be the lengths of one of the features.

## What are my concerns with this change?
1. Outputs from `__assert_fail` go to `stderr` whereas `printf` writes to `stdout`. This is not the usual debugging flow where all logs can be found in `stderr`. I could not find a way to redirect `printf` to stderr or `__assert_fail` to stdout
2. Two checks happen instead of one in the error path. I wanted to preserve the semantics of what happens inside `__assert_fail`.
3. I have not seen this pattern in other PyTorch kernels but `repeat_interleave` with three arguments seems special in other ways too.

Test Plan:
* Built an ephemeral package with my changes:
https://www.internalfb.com/intern/servicelab/build/736441058/

* Verified that a job with these changes indeed prints out the expected message to stdout: https://fburl.com/mlhub/jgbqk8eg

* I will export to GH and run CI/CD tests.

Rollback Plan:
steps:
  - manual.note:
      content: >-
        Just reverting this diff should be sufficient. Since this change is in
        CUDA kernels, I do not believe there is a way to change the error
        message via a JK.

Reviewed By: mradmila

Differential Revision: D77904753

Pull Request resolved: pytorch#157996
Approved by: https://github.com/ngimel, https://github.com/eqy

Author: drdarshan

aten/src/ATen/native/cuda/Repeat.cu

@@ -17,7 +17,13 @@ __global__ static void compute_cuda_kernel(
     index_t* result_ptr,
     int64_t size,
     int64_t result_size) {
-  CUDA_KERNEL_ASSERT(result_size == cumsum_ptr[size - 1]);
+  if (C10_UNLIKELY((result_size != cumsum_ptr[size - 1]))) {
+    printf("%s:%d:%s: block: [%d,%d,%d], thread: [%d,%d,%d] "
+      "Invalid input! In `repeat_interleave`, the `output_size` argument (%ld) must be the same as the sum of the elements in the `repeats` tensor (%ld).\n",
+      __FILE__, __LINE__, __func__,blockIdx.x, blockIdx.y, blockIdx.z, threadIdx.x, threadIdx.y, threadIdx.z, result_size, cumsum_ptr[size - 1 ]);
+    CUDA_KERNEL_ASSERT(result_size == cumsum_ptr[size - 1])
+  }
+
   int64_t idx = ((int64_t) blockIdx.x) * blockDim.x + threadIdx.x;
   int64_t stride = (blockDim.x * gridDim.x) / C10_WARP_SIZE;
   int warp_id = idx / C10_WARP_SIZE;