Re-organize SLL ops, pt 6

fbgemm_gpu/fbgemm_gpu/sll/__init__.py

@@ -34,12 +34,8 @@
 )
 
 from fbgemm_gpu.sll.triton_sll import (  # noqa F401
-    array_jagged_bmm_jagged_out,
-    dense_jagged_cat_jagged_out,
     jagged2_to_padded_dense,
-    # jagged_dense_bmm,
     jagged_dense_elementwise_mul_jagged_out,
-    jagged_jagged_bmm_jagged_out,
     triton_jagged_self_substraction_jagged_out,
 )
 
@@ -269,9 +265,6 @@
 
 # pyre-ignore[5]
 sll_gpu_registrations = {
-    "sll_dense_jagged_cat_jagged_out": {
-        "CUDA": dense_jagged_cat_jagged_out,
-    },
     "sll_jagged_self_substraction_jagged_out": {
         "CUDA": triton_jagged_self_substraction_jagged_out,
     },
@@ -283,14 +276,6 @@
         "CUDA": jagged_dense_elementwise_mul_jagged_out,
         "AutogradCUDA": jagged_dense_elementwise_mul_jagged_out,
     },
-    "sll_array_jagged_bmm_jagged_out": {
-        "CUDA": array_jagged_bmm_jagged_out,
-        "AutogradCUDA": array_jagged_bmm_jagged_out,
-    },
-    "sll_jagged_jagged_bmm_jagged_out": {
-        "CUDA": jagged_jagged_bmm_jagged_out,
-        "AutogradCUDA": jagged_jagged_bmm_jagged_out,
-    },
 }
 
 for op_name, dispatches in sll_cpu_registrations.items():

fbgemm_gpu/fbgemm_gpu/sll/triton/__init__.py

@@ -7,13 +7,26 @@
 
 # pyre-strict
 
+from fbgemm_gpu.sll.triton.triton_dense_jagged_cat_jagged_out import (
+    dense_jagged_cat_jagged_out,
+)
+
 from fbgemm_gpu.sll.triton.triton_jagged_bmm import (  # noqa F401
     jagged_dense_bmm,
     jagged_jagged_bmm,
     JaggedDenseBmm,  # noqa F401
     JaggedJaggedBmm,  # noqa F401
 )
 
+from fbgemm_gpu.sll.triton.triton_jagged_bmm_jagged_out import (  # noqa F401
+    array_jagged_bmm_jagged_out,
+    ArrayJaggedBmmNopadding,  # noqa F401
+    jagged_jagged_bmm_jagged_out,
+    JaggedJaggedBmmNoPadding,  # noqa F401
+    triton_array_jagged_bmm_jagged_out,  # noqa F401
+    triton_jagged_jagged_bmm_jagged_out,  # noqa F401
+)
+
 from fbgemm_gpu.sll.triton.triton_jagged_dense_elementwise_add import (  # noqa F401
     jagged_dense_elementwise_add,
     JaggedDenseAdd,  # noqa F401
@@ -43,6 +56,9 @@
 
 # pyre-ignore[5]
 op_registrations = {
+    "sll_dense_jagged_cat_jagged_out": {
+        "CUDA": dense_jagged_cat_jagged_out,
+    },
     "sll_jagged_dense_bmm": {
         "CUDA": jagged_dense_bmm,
         "AutogradCUDA": jagged_dense_bmm,
@@ -51,6 +67,14 @@
         "CUDA": jagged_jagged_bmm,
         "AutogradCUDA": jagged_jagged_bmm,
     },
+    "sll_array_jagged_bmm_jagged_out": {
+        "CUDA": array_jagged_bmm_jagged_out,
+        "AutogradCUDA": array_jagged_bmm_jagged_out,
+    },
+    "sll_jagged_jagged_bmm_jagged_out": {
+        "CUDA": jagged_jagged_bmm_jagged_out,
+        "AutogradCUDA": jagged_jagged_bmm_jagged_out,
+    },
     "sll_jagged_softmax": {
         "CUDA": jagged_softmax,
         "AutogradCUDA": jagged_softmax,

fbgemm_gpu/fbgemm_gpu/sll/triton/triton_dense_jagged_cat_jagged_out.py

@@ -0,0 +1,72 @@
+# Copyright (c) Meta Platforms, Inc. and affiliates.
+# All rights reserved.
+#
+# This source code is licensed under the BSD-style license found in the
+# LICENSE file in the root directory of this source tree.
+
+# pyre-unsafe
+
+import torch
+import triton
+import triton.language as tl
+
+
+@triton.jit
+def dense_jagged_cat_jagged_out_kernel(
+    a_ptr,  # dense
+    b_ptr,  # jagged
+    c_ptr,  # jagged
+    b_offsets_ptr,
+    c_offsets_ptr,
+    max_seq_len,
+    BLOCK_SIZE: tl.constexpr,
+):
+    pid_batch = tl.program_id(0)
+    b_start = tl.load(b_offsets_ptr + pid_batch)
+    b_end = tl.load(b_offsets_ptr + pid_batch + 1)
+    c_start = b_start + pid_batch
+    N = b_end - b_start
+    N = tl.minimum(N, max_seq_len)
+
+    a = tl.load(a_ptr + pid_batch)
+    tl.store(c_ptr + c_start, a)
+
+    offs_k = tl.arange(0, BLOCK_SIZE)
+    for k in range(0, N, BLOCK_SIZE):
+        b_offset = k + offs_k
+        b_ptrs = b_ptr + b_start + b_offset
+        b = tl.load(b_ptrs, mask=b_offset < N, other=0.0)
+        tl.store(c_ptr + c_start + 1 + b_offset, b, mask=b_offset < N)
+    tl.store(c_offsets_ptr + pid_batch, b_start + pid_batch)
+
+
+def dense_jagged_cat_jagged_out(
+    a: torch.Tensor,
+    b: torch.Tensor,
+    b_offsets: torch.Tensor,
+    max_seq_len: int,
+):
+    assert a.is_contiguous()
+    assert b.is_contiguous()
+    assert b_offsets.is_contiguous()
+    B = a.size(0)
+    BLOCK_SIZE = 128
+    c = torch.zeros(b.size(0) + a.size(0), dtype=a.dtype, device=a.device)
+    c_offsets = torch.empty(
+        b_offsets.size(0), dtype=b_offsets.dtype, device=b_offsets.device
+    )  # B + 1
+
+    dense_jagged_cat_jagged_out_kernel[(B,)](
+        a,
+        b,
+        c,
+        b_offsets,
+        c_offsets,
+        max_seq_len,
+        # pyre-fixme[6]: For 7th argument expected `constexpr` but got `int`.
+        BLOCK_SIZE,
+    )
+
+    c_offsets[-1] = b_offsets[-1] + B
+
+    return c, c_offsets