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Fix cuda kernel for seq_len < 8192 #3

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Dec 7, 2022
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Fix cuda kernel for seq_len < 8192 #3

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20 changes: 18 additions & 2 deletions megatron/fused_kernels/scaled_upper_triang_masked_softmax.h
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Original file line number Diff line number Diff line change
Expand Up @@ -341,7 +341,7 @@ void dispatch_scaled_upper_triang_masked_softmax_forward(
int softmax_elements_stride,
int attn_batches)
{
TORCH_INTERNAL_ASSERT(softmax_elements >= 0 && softmax_elements <= 2048 );
TORCH_INTERNAL_ASSERT(softmax_elements >= 0 && softmax_elements <= 8192 );
if (softmax_elements == 0) {
return;
} else {
Expand Down Expand Up @@ -416,6 +416,14 @@ void dispatch_scaled_upper_triang_masked_softmax_forward(
scaled_upper_triang_masked_softmax_warp_forward<input_t, output_t, acc_t, 11>
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(dst, src, scale, batch_count, softmax_elements_stride, softmax_elements);
break;
case 12: // 4096
scaled_upper_triang_masked_softmax_warp_forward<input_t, output_t, acc_t, 12>
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(dst, src, scale, batch_count, softmax_elements_stride, softmax_elements);
break;
case 13: // 8192
scaled_upper_triang_masked_softmax_warp_forward<input_t, output_t, acc_t, 13>
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(dst, src, scale, batch_count, softmax_elements_stride, softmax_elements);
break;
default:
break;
}
Expand All @@ -432,7 +440,7 @@ void dispatch_scaled_upper_triang_masked_softmax_backward(
int softmax_elements_stride,
int attn_batches)
{
TORCH_INTERNAL_ASSERT( softmax_elements >= 0 && softmax_elements <= 2048 );
TORCH_INTERNAL_ASSERT( softmax_elements >= 0 && softmax_elements <= 8192 );
if (softmax_elements == 0) {
return;
} else {
Expand Down Expand Up @@ -507,6 +515,14 @@ void dispatch_scaled_upper_triang_masked_softmax_backward(
scaled_upper_triang_masked_softmax_warp_backward<input_t, output_t, acc_t, 11>
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(grad_input, grad, output, scale, batch_count, softmax_elements_stride, softmax_elements);
break;
case 12: // 4096
scaled_upper_triang_masked_softmax_warp_backward<input_t, output_t, acc_t, 12>
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(grad_input, grad, output, scale, batch_count, softmax_elements_stride, softmax_elements);
break;
case 13: // 8192
scaled_upper_triang_masked_softmax_warp_backward<input_t, output_t, acc_t, 13>
<<<blocks, threads, 0, at::cuda::getCurrentCUDAStream()>>>(grad_input, grad, output, scale, batch_count, softmax_elements_stride, softmax_elements);
break;
default:
break;
}
Expand Down
2 changes: 1 addition & 1 deletion megatron/fused_kernels/scaled_upper_triang_masked_softmax_cuda.cu
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Expand Up @@ -37,7 +37,7 @@ torch::Tensor fwd_cuda(
// input is a 3d tensor with dimensions [attn_batches, seq_len, seq_len]
const int attn_batches = input.size(0);
const int seq_len = input.size(1);
TORCH_INTERNAL_ASSERT(seq_len <= 2048);
TORCH_INTERNAL_ASSERT(seq_len <= 8192);

// Output
auto act_options = input.options().requires_grad(false);
Expand Down
4 changes: 4 additions & 0 deletions megatron/fused_kernels/tests/test_fused_kernels.py
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Expand Up @@ -3,6 +3,10 @@
import torch
from torch.nn import LayerNorm

import sys
# add to path
sys.path.append("/home/nouamane/projects/Megatron-DeepSpeed/")
import megatron
from megatron.model.enums import AttnMaskType
from megatron.model.fused_layer_norm import MixedFusedLayerNorm
from megatron.model.fused_softmax import FusedScaleMaskSoftmax
Expand Down
2 changes: 1 addition & 1 deletion megatron/initialize.py
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Expand Up @@ -194,7 +194,7 @@ def _compile_dependencies():
args.micro_batch_size
# Constraints on sequence length and attn_batch_size to enable warp based
# optimization and upper triangular optimization (for causal mask)
custom_kernel_constraint = seq_len > 16 and seq_len <=2048 and \
custom_kernel_constraint = seq_len > 16 and seq_len <=8192 and \
seq_len % 4 == 0 and attn_batch_size % 4 == 0
# Print a warning.
if not ((args.fp16 or args.bf16) and
Expand Down
4 changes: 2 additions & 2 deletions megatron/model/fused_softmax.py
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Expand Up @@ -167,11 +167,11 @@ def is_kernel_available(self, mask, b, np, sq, sk):
if (
self.scaled_masked_softmax_fusion # user want to fuse
and self.input_in_float16 # input must be fp16
and 16 < sk <= 4096 # sk must be 16 ~ 4096
and 16 < sk <= 8192 # sk must be 16 ~ 8192
and sq % 4 == 0 # sq must be divisor of 4
and attn_batches % 4 == 0 # np * b must be divisor of 4
):
if 0 <= sk <= 4096:
if 0 <= sk <= 8192:
batch_per_block = self.get_batch_per_block(sq, sk, b, np)

if self.attn_mask_type == AttnMaskType.causal:
Expand Down