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[[package]] name = "accessible-pygments" diff --git a/security_scanning/examples/apps/poetry.lock b/security_scanning/examples/apps/poetry.lock index 0820bdd6f561..186de5aa0aa2 100644 --- a/security_scanning/examples/apps/poetry.lock +++ b/security_scanning/examples/apps/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 2.3.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.3.4 and should not be changed by hand. [[package]] name = "annotated-types" diff --git a/security_scanning/examples/auto_deploy/poetry.lock b/security_scanning/examples/auto_deploy/poetry.lock index abe0bb98320e..a6ecfb2e2051 100644 --- a/security_scanning/examples/auto_deploy/poetry.lock +++ b/security_scanning/examples/auto_deploy/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 2.3.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.3.4 and should not be changed by hand. 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[[package]] name = "absl-py" @@ -1949,14 +1949,14 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<8)"] [[package]] name = "rich" -version = "14.3.4" +version = "15.0.0" description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal" optional = false -python-versions = ">=3.8.0" +python-versions = ">=3.9.0" groups = ["main"] files = [ - {file = "rich-14.3.4-py3-none-any.whl", hash = "sha256:07e7adb4690f68864777b1450859253bed81a99a31ac321ac1817b2313558952"}, - {file = "rich-14.3.4.tar.gz", hash = "sha256:817e02727f2b25b40ef56f5aa2217f400c8489f79ca8f46ea2b70dd5e14558a9"}, + {file = "rich-15.0.0-py3-none-any.whl", hash = "sha256:33bd4ef74232fb73fe9279a257718407f169c09b78a87ad3d296f548e27de0bb"}, + {file = "rich-15.0.0.tar.gz", hash = "sha256:edd07a4824c6b40189fb7ac9bc4c52536e9780fbbfbddf6f1e2502c31b068c36"}, ] [package.dependencies] diff --git a/security_scanning/examples/models/contrib/stdit/poetry.lock b/security_scanning/examples/models/contrib/stdit/poetry.lock index 72cecfd07442..40e1e13fc6ee 100644 --- a/security_scanning/examples/models/contrib/stdit/poetry.lock +++ b/security_scanning/examples/models/contrib/stdit/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 2.3.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.3.4 and should not be changed by hand. 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[[package]] name = "absl-py" @@ -1967,14 +1967,14 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<8)"] [[package]] name = "rich" -version = "14.3.4" +version = "15.0.0" description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal" optional = false -python-versions = ">=3.8.0" +python-versions = ">=3.9.0" groups = ["main"] files = [ - {file = "rich-14.3.4-py3-none-any.whl", hash = "sha256:07e7adb4690f68864777b1450859253bed81a99a31ac321ac1817b2313558952"}, - {file = "rich-14.3.4.tar.gz", hash = "sha256:817e02727f2b25b40ef56f5aa2217f400c8489f79ca8f46ea2b70dd5e14558a9"}, + {file = "rich-15.0.0-py3-none-any.whl", hash = "sha256:33bd4ef74232fb73fe9279a257718407f169c09b78a87ad3d296f548e27de0bb"}, + {file = "rich-15.0.0.tar.gz", hash = "sha256:edd07a4824c6b40189fb7ac9bc4c52536e9780fbbfbddf6f1e2502c31b068c36"}, ] [package.dependencies] diff --git a/security_scanning/examples/models/core/gpt/poetry.lock b/security_scanning/examples/models/core/gpt/poetry.lock index 0677b5c0f4b3..942a103d0ab3 100644 --- a/security_scanning/examples/models/core/gpt/poetry.lock +++ b/security_scanning/examples/models/core/gpt/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 2.3.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.3.4 and should not be changed by hand. [[package]] name = "absl-py" @@ -1949,14 +1949,14 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<8)"] [[package]] name = "rich" -version = "14.3.4" +version = "15.0.0" description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal" optional = false -python-versions = ">=3.8.0" +python-versions = ">=3.9.0" groups = ["main"] files = [ - {file = "rich-14.3.4-py3-none-any.whl", hash = "sha256:07e7adb4690f68864777b1450859253bed81a99a31ac321ac1817b2313558952"}, - {file = "rich-14.3.4.tar.gz", hash = "sha256:817e02727f2b25b40ef56f5aa2217f400c8489f79ca8f46ea2b70dd5e14558a9"}, + {file = "rich-15.0.0-py3-none-any.whl", hash = "sha256:33bd4ef74232fb73fe9279a257718407f169c09b78a87ad3d296f548e27de0bb"}, + {file = "rich-15.0.0.tar.gz", hash = "sha256:edd07a4824c6b40189fb7ac9bc4c52536e9780fbbfbddf6f1e2502c31b068c36"}, ] [package.dependencies] diff --git a/security_scanning/examples/models/core/internlm2/poetry.lock b/security_scanning/examples/models/core/internlm2/poetry.lock index 04eb8296cb6d..64507dfd0919 100644 --- a/security_scanning/examples/models/core/internlm2/poetry.lock +++ b/security_scanning/examples/models/core/internlm2/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 2.3.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.3.4 and should not be changed by hand. [[package]] name = "einops" diff --git a/security_scanning/examples/models/core/llama/poetry.lock b/security_scanning/examples/models/core/llama/poetry.lock index 3f506d839866..c931c47ff988 100644 --- a/security_scanning/examples/models/core/llama/poetry.lock +++ b/security_scanning/examples/models/core/llama/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 2.3.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.3.4 and should not be changed by hand. 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[[package]] name = "absl-py" @@ -1865,14 +1865,14 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<8)"] [[package]] name = "rich" -version = "14.3.4" +version = "15.0.0" description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal" optional = false -python-versions = ">=3.8.0" +python-versions = ">=3.9.0" groups = ["main"] files = [ - {file = "rich-14.3.4-py3-none-any.whl", hash = "sha256:07e7adb4690f68864777b1450859253bed81a99a31ac321ac1817b2313558952"}, - {file = "rich-14.3.4.tar.gz", hash = "sha256:817e02727f2b25b40ef56f5aa2217f400c8489f79ca8f46ea2b70dd5e14558a9"}, + {file = "rich-15.0.0-py3-none-any.whl", hash = "sha256:33bd4ef74232fb73fe9279a257718407f169c09b78a87ad3d296f548e27de0bb"}, + {file = "rich-15.0.0.tar.gz", hash = "sha256:edd07a4824c6b40189fb7ac9bc4c52536e9780fbbfbddf6f1e2502c31b068c36"}, ] [package.dependencies] diff --git a/security_scanning/examples/models/core/mixtral/poetry.lock b/security_scanning/examples/models/core/mixtral/poetry.lock index c0888e88048c..835e4481135c 100644 --- a/security_scanning/examples/models/core/mixtral/poetry.lock +++ b/security_scanning/examples/models/core/mixtral/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 2.3.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.3.4 and should not be changed by hand. [[package]] name = "accelerate" diff --git a/security_scanning/examples/models/core/mllama/poetry.lock b/security_scanning/examples/models/core/mllama/poetry.lock index d177080d7443..faa2d5d24357 100644 --- a/security_scanning/examples/models/core/mllama/poetry.lock +++ b/security_scanning/examples/models/core/mllama/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 2.3.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.3.4 and should not be changed by hand. [[package]] name = "annotated-types" @@ -1510,14 +1510,14 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<8)"] [[package]] name = "rich" -version = "14.3.4" +version = "15.0.0" description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal" optional = false -python-versions = ">=3.8.0" +python-versions = ">=3.9.0" groups = ["main"] files = [ - {file = "rich-14.3.4-py3-none-any.whl", hash = "sha256:07e7adb4690f68864777b1450859253bed81a99a31ac321ac1817b2313558952"}, - {file = "rich-14.3.4.tar.gz", hash = "sha256:817e02727f2b25b40ef56f5aa2217f400c8489f79ca8f46ea2b70dd5e14558a9"}, + {file = "rich-15.0.0-py3-none-any.whl", hash = "sha256:33bd4ef74232fb73fe9279a257718407f169c09b78a87ad3d296f548e27de0bb"}, + {file = "rich-15.0.0.tar.gz", hash = "sha256:edd07a4824c6b40189fb7ac9bc4c52536e9780fbbfbddf6f1e2502c31b068c36"}, ] [package.dependencies] diff --git a/security_scanning/examples/models/core/nemotron/poetry.lock b/security_scanning/examples/models/core/nemotron/poetry.lock index 5a5dc1df7703..4c2d02fbb45c 100644 --- a/security_scanning/examples/models/core/nemotron/poetry.lock +++ b/security_scanning/examples/models/core/nemotron/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 2.3.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.3.4 and should not be changed by hand. [[package]] name = "absl-py" @@ -1949,14 +1949,14 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<8)"] [[package]] name = "rich" -version = "14.3.4" +version = "15.0.0" description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal" optional = false -python-versions = ">=3.8.0" +python-versions = ">=3.9.0" groups = ["main"] files = [ - {file = "rich-14.3.4-py3-none-any.whl", hash = "sha256:07e7adb4690f68864777b1450859253bed81a99a31ac321ac1817b2313558952"}, - {file = "rich-14.3.4.tar.gz", hash = "sha256:817e02727f2b25b40ef56f5aa2217f400c8489f79ca8f46ea2b70dd5e14558a9"}, + {file = "rich-15.0.0-py3-none-any.whl", hash = "sha256:33bd4ef74232fb73fe9279a257718407f169c09b78a87ad3d296f548e27de0bb"}, + {file = "rich-15.0.0.tar.gz", hash = "sha256:edd07a4824c6b40189fb7ac9bc4c52536e9780fbbfbddf6f1e2502c31b068c36"}, ] [package.dependencies] diff --git a/security_scanning/examples/models/core/phi/poetry.lock b/security_scanning/examples/models/core/phi/poetry.lock index cb272a8e8a27..eafff70b6170 100644 --- a/security_scanning/examples/models/core/phi/poetry.lock +++ b/security_scanning/examples/models/core/phi/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 2.3.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.3.4 and should not be changed by hand. [[package]] name = "absl-py" @@ -1961,14 +1961,14 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<8)"] [[package]] name = "rich" -version = "14.3.4" +version = "15.0.0" description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal" optional = false -python-versions = ">=3.8.0" +python-versions = ">=3.9.0" groups = ["main"] files = [ - {file = "rich-14.3.4-py3-none-any.whl", hash = "sha256:07e7adb4690f68864777b1450859253bed81a99a31ac321ac1817b2313558952"}, - {file = "rich-14.3.4.tar.gz", hash = "sha256:817e02727f2b25b40ef56f5aa2217f400c8489f79ca8f46ea2b70dd5e14558a9"}, + {file = "rich-15.0.0-py3-none-any.whl", hash = "sha256:33bd4ef74232fb73fe9279a257718407f169c09b78a87ad3d296f548e27de0bb"}, + {file = "rich-15.0.0.tar.gz", hash = "sha256:edd07a4824c6b40189fb7ac9bc4c52536e9780fbbfbddf6f1e2502c31b068c36"}, ] [package.dependencies] diff --git a/security_scanning/examples/models/core/qwen/poetry.lock b/security_scanning/examples/models/core/qwen/poetry.lock index bffc37aeed84..002fb0c53564 100644 --- a/security_scanning/examples/models/core/qwen/poetry.lock +++ b/security_scanning/examples/models/core/qwen/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 2.3.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.3.4 and should not be changed by hand. [[package]] name = "absl-py" @@ -2697,14 +2697,14 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<8)"] [[package]] name = "rich" -version = "14.3.4" +version = "15.0.0" description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal" optional = false -python-versions = ">=3.8.0" +python-versions = ">=3.9.0" groups = ["main"] files = [ - {file = "rich-14.3.4-py3-none-any.whl", hash = "sha256:07e7adb4690f68864777b1450859253bed81a99a31ac321ac1817b2313558952"}, - {file = "rich-14.3.4.tar.gz", hash = "sha256:817e02727f2b25b40ef56f5aa2217f400c8489f79ca8f46ea2b70dd5e14558a9"}, + {file = "rich-15.0.0-py3-none-any.whl", hash = "sha256:33bd4ef74232fb73fe9279a257718407f169c09b78a87ad3d296f548e27de0bb"}, + {file = "rich-15.0.0.tar.gz", hash = "sha256:edd07a4824c6b40189fb7ac9bc4c52536e9780fbbfbddf6f1e2502c31b068c36"}, ] [package.dependencies] diff --git a/security_scanning/examples/models/core/qwen2audio/poetry.lock b/security_scanning/examples/models/core/qwen2audio/poetry.lock index cd4a9dfbd4e4..adda6f6fc67c 100644 --- a/security_scanning/examples/models/core/qwen2audio/poetry.lock +++ b/security_scanning/examples/models/core/qwen2audio/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 2.3.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.3.4 and should not be changed by hand. 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by Poetry 2.3.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.3.4 and should not be changed by hand. [[package]] name = "contourpy" diff --git a/security_scanning/triton_backend/poetry.lock b/security_scanning/triton_backend/poetry.lock index d1eca3f029a7..382f98fb318b 100644 --- a/security_scanning/triton_backend/poetry.lock +++ b/security_scanning/triton_backend/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 2.3.3 and should not be changed by hand. +# This file is automatically @generated by Poetry 2.3.4 and should not be changed by hand. [[package]] name = "aiohappyeyeballs" diff --git a/tensorrt_llm/_torch/auto_deploy/custom_ops/attention/onnx_attention.py b/tensorrt_llm/_torch/auto_deploy/custom_ops/attention/onnx_attention.py index c729c27fe4f2..8c08aa160118 100644 --- a/tensorrt_llm/_torch/auto_deploy/custom_ops/attention/onnx_attention.py +++ b/tensorrt_llm/_torch/auto_deploy/custom_ops/attention/onnx_attention.py @@ -29,7 +29,9 @@ @torch.library.custom_op("auto_deploy::torch_onnx_attention_plugin", mutates_args=()) def attention_plugin( # Inputs - qkv: torch.Tensor, + q: torch.Tensor, + k: torch.Tensor, + v: torch.Tensor, past_key_values: torch.Tensor, context_lengths: torch.Tensor, rope_rotary_cos_sin: torch.Tensor, @@ -39,6 +41,8 @@ def attention_plugin( head_size: int, num_kv_heads: int, num_q_heads: int, + enable_fp8_kv_cache: int = 0, + sliding_window_size: int = -1, ) -> Tuple[torch.Tensor, torch.Tensor]: """Fused attention operation with integrated RoPE (Rotary Position Embedding). @@ -48,10 +52,11 @@ def attention_plugin( Note: This is a placeholder implementation for ONNX export. The actual computation - is performed by the backend runtime (e.g., TensorRT, EdgeLLM + is performed by the backend runtime (e.g., TensorRT, EdgeLLM). Args: - qkv: Concatenated query, key, value tensor of shape - [batch_size, seq_len, (num_q_heads + 2 * num_kv_heads) * head_size]. + q: Query tensor of shape [batch_size, seq_len, num_q_heads * head_size]. + k: Key tensor of shape [batch_size, seq_len, num_kv_heads * head_size]. + v: Value tensor of shape [batch_size, seq_len, num_kv_heads * head_size]. past_key_values: KV-cache tensor of shape [batch_size, 2, num_kv_heads, past_seq_len, head_size]. context_lengths: Sequence lengths for each batch element, shape [batch_size]. @@ -63,6 +68,8 @@ def attention_plugin( head_size: Dimension of each attention head. num_kv_heads: Number of key-value heads (for grouped-query attention). num_q_heads: Number of query heads. + enable_fp8_kv_cache: Whether to use FP8 KV cache (0 or 1). Default 0. + sliding_window_size: Sliding window size for attention (-1 = no window). Default -1. Returns: A tuple containing: @@ -71,12 +78,14 @@ def attention_plugin( - present_key_values: Updated KV-cache tensor of shape [batch_size, 2, num_kv_heads, present_seq_len, head_size]. """ - return qkv.new_empty(0), past_key_values.new_empty(0) + return q.new_empty(0), past_key_values.new_empty(0) @attention_plugin.register_fake def attention_plugin_fake( - qkv: torch.Tensor, + q: torch.Tensor, + k: torch.Tensor, + v: torch.Tensor, past_key_values: torch.Tensor, context_lengths: torch.Tensor, rope_rotary_cos_sin: torch.Tensor, @@ -85,6 +94,8 @@ def attention_plugin_fake( head_size: int, num_kv_heads: int, num_q_heads: int, + enable_fp8_kv_cache: int = 0, + sliding_window_size: int = -1, ) -> Tuple[torch.Tensor, torch.Tensor]: """Fake implementation of attention_plugin for torch.compile shape inference. @@ -92,7 +103,9 @@ def attention_plugin_fake( enabling torch.compile to trace through the custom operation. Args: - qkv: Concatenated QKV tensor. + q: Query tensor. + k: Key tensor. + v: Value tensor. past_key_values: Previous KV-cache tensor. context_lengths: Sequence lengths per batch. rope_rotary_cos_sin: RoPE embedding values. @@ -101,18 +114,20 @@ def attention_plugin_fake( head_size: Attention head dimension. num_kv_heads: Number of KV heads. num_q_heads: Number of query heads. + enable_fp8_kv_cache: FP8 KV cache flag (unused in shape). + sliding_window_size: Sliding window size (unused in shape). Returns: Tuple of empty tensors with correct shapes for attention output and present KV-cache. """ - batch_size = qkv.size(0) - seq_len = qkv.size(1) + batch_size = q.size(0) + seq_len = q.size(1) past_len = past_key_values.size(3) present_kv_len = seq_len + past_len attn_shape = (batch_size, seq_len, num_q_heads, head_size) present_kv_shape = (batch_size, 2, num_kv_heads, present_kv_len, head_size) - return torch.empty(attn_shape, device=qkv.device, dtype=qkv.dtype), torch.empty( + return torch.empty(attn_shape, device=q.device, dtype=q.dtype), torch.empty( present_kv_shape, device=past_key_values.device, dtype=past_key_values.dtype ) diff --git a/tensorrt_llm/_torch/auto_deploy/transform/library/_onnx_schemas.py b/tensorrt_llm/_torch/auto_deploy/transform/library/_onnx_schemas.py index 0a13f780f815..3c21db64ba8c 100644 --- a/tensorrt_llm/_torch/auto_deploy/transform/library/_onnx_schemas.py +++ b/tensorrt_llm/_torch/auto_deploy/transform/library/_onnx_schemas.py @@ -85,8 +85,18 @@ doc="Fused RoPE + Attention operation for efficient inference.", inputs=[ defs.OpSchema.FormalParameter( - name="qkv", - description="Concatenated Q, K, V tensors in shape [batch, seq_len, qkv_hidden_size]", + name="q", + description="Query tensor in shape [batch, seq_len, num_q_heads * head_size]", + type_str="T", + ), + defs.OpSchema.FormalParameter( + name="k", + description="Key tensor in shape [batch, seq_len, num_kv_heads * head_size]", + type_str="T", + ), + defs.OpSchema.FormalParameter( + name="v", + description="Value tensor in shape [batch, seq_len, num_kv_heads * head_size]", type_str="T", ), defs.OpSchema.FormalParameter( @@ -159,6 +169,18 @@ description="Number of query heads.", required=True, ), + defs.OpSchema.Attribute( + name="enable_fp8_kv_cache", + type=defs.OpSchema.AttrType.INT, + description="Whether to use FP8 KV cache (0 or 1). Default 0.", + required=False, + ), + defs.OpSchema.Attribute( + name="sliding_window_size", + type=defs.OpSchema.AttrType.INT, + description="Sliding window size for attention (-1 = no window). Default -1.", + required=False, + ), ], ) diff --git a/tensorrt_llm/_torch/auto_deploy/transform/library/export_to_onnx.py b/tensorrt_llm/_torch/auto_deploy/transform/library/export_to_onnx.py index 22d3cf4d499f..9cd844ce604f 100644 --- a/tensorrt_llm/_torch/auto_deploy/transform/library/export_to_onnx.py +++ b/tensorrt_llm/_torch/auto_deploy/transform/library/export_to_onnx.py @@ -81,7 +81,9 @@ def _translate_gather_nd_op(data: ir.Tensor, indices: ir.Tensor, batch_dims: int def _translate_rope_attention_op( - qkv: ir.Tensor, + q: ir.Tensor, + k: ir.Tensor, + v: ir.Tensor, past_key_values: ir.Tensor, context_lengths: ir.Tensor, rope_rotary_cos_sin: ir.Tensor, @@ -90,6 +92,8 @@ def _translate_rope_attention_op( head_size: int, num_kv_heads: int, num_q_heads: int, + enable_fp8_kv_cache: int = 0, + sliding_window_size: int = -1, ): """ ONNX custom op translation function for AttentionPlugin. @@ -103,7 +107,9 @@ def _translate_rope_attention_op( """ # Call the custom op from the trt domain return _onnx_schemas.trt_opset.AttentionPlugin( - qkv, + q, + k, + v, past_key_values, context_lengths, rope_rotary_cos_sin, @@ -112,6 +118,8 @@ def _translate_rope_attention_op( head_size=head_size, num_kv_heads=num_kv_heads, num_q_heads=num_q_heads, + enable_fp8_kv_cache=enable_fp8_kv_cache, + sliding_window_size=sliding_window_size, ) diff --git a/tensorrt_llm/_torch/auto_deploy/transform/library/fuse_rope_attention.py b/tensorrt_llm/_torch/auto_deploy/transform/library/fuse_rope_attention.py index bfbacea513bb..ded3c2b30b88 100644 --- a/tensorrt_llm/_torch/auto_deploy/transform/library/fuse_rope_attention.py +++ b/tensorrt_llm/_torch/auto_deploy/transform/library/fuse_rope_attention.py @@ -345,11 +345,10 @@ def _perform_replacement( For each matched pattern, this method: 1. Creates a past_key_values input placeholder for KV-cache 2. Reshape Q, K, V to (batch_size, seq_len, -1) - 3. Concatenates reshaped Q, K, V tensors into a single QKV tensor - 4. Inserts the fused AttentionPlugin operation - 5. Creates getitem nodes to extract attention output and present KV-cache - 6. Replaces the original attention node with the fused output - 7. Adds present_key_values to graph outputs + 3. Cast Q, K, V to float16 and insert the fused AttentionPlugin (q, k, v separate) + 4. Creates getitem nodes to extract attention output and present KV-cache + 5. Replaces the original attention node with the fused output + 6. Adds present_key_values to graph outputs Args: gm: The GraphModule being transformed. @@ -410,28 +409,22 @@ def _perform_replacement( f"Reshaped Q, K, V to (batch_size, seq_len, -1): {q_node.name}, {k_node.name}, {v_node.name}" ) - # 3. Concatenate reshaped Q, K, V to (batch_size, seq_len, -1) - with graph.inserting_before(match.attn_node): - qkv_node = graph.call_function( - torch.ops.aten.cat.default, args=([q_node, k_node, v_node], -1) - ) - - ad_logger.debug(f"Created qkv concat node: {qkv_node.name}") - - # 4. Create AttentionPlugin node + # 3. Cast Q, K, V to float16 and create AttentionPlugin node (q, k, v as separate inputs) enable_tree_attention = 0 head_dim = match.head_dim num_kv_heads = match.num_kv_heads num_q_heads = match.num_q_heads with graph.inserting_before(match.attn_node): - cast_node = graph.call_function( - torch.ops.aten.to.dtype, args=(qkv_node, torch.float16) - ) + cast_q = graph.call_function(torch.ops.aten.to.dtype, args=(q_node, torch.float16)) + cast_k = graph.call_function(torch.ops.aten.to.dtype, args=(k_node, torch.float16)) + cast_v = graph.call_function(torch.ops.aten.to.dtype, args=(v_node, torch.float16)) rope_attn_node = graph.call_function( torch.ops.auto_deploy.torch_onnx_attention_plugin.default, args=( - cast_node, + cast_q, + cast_k, + cast_v, past_key_values_node, context_lengths_node, rope_rotary_cos_sin_node, @@ -441,6 +434,7 @@ def _perform_replacement( num_kv_heads, num_q_heads, ), + kwargs={"enable_fp8_kv_cache": 0, "sliding_window_size": -1}, ) ad_logger.debug(f"Created AttentionPlugin node: {rope_attn_node.name}") diff --git a/tensorrt_llm/_torch/modules/fused_moe/fused_moe_cute_dsl.py b/tensorrt_llm/_torch/modules/fused_moe/fused_moe_cute_dsl.py index 8036819993cc..97c3c9072ca8 100644 --- a/tensorrt_llm/_torch/modules/fused_moe/fused_moe_cute_dsl.py +++ b/tensorrt_llm/_torch/modules/fused_moe/fused_moe_cute_dsl.py @@ -982,7 +982,8 @@ def forward_chunk( def load_weights(self, weights: List[Dict], allow_partial_loading: bool = False): - super().load_weights(weights, allow_partial_loading) + super().load_weights(weights, + allow_partial_loading=allow_partial_loading) dwdp_handle_collector = getattr(self, "dwdp_handle_collector", None) if dwdp_handle_collector is not None: dwdp_handle_collector.register_weights(self) diff --git a/tensorrt_llm/_torch/pyexecutor/_util.py b/tensorrt_llm/_torch/pyexecutor/_util.py index ecfcab0afa79..c4d714cd1e5b 100644 --- a/tensorrt_llm/_torch/pyexecutor/_util.py +++ b/tensorrt_llm/_torch/pyexecutor/_util.py @@ -1024,6 +1024,7 @@ def _create_kv_cache_manager( spec_config=spec_config, is_estimating_kv_cache=estimating_kv_cache, execution_stream=execution_stream, + model_type="nemotron_hybrid", ) elif is_qwen3_hybrid(config): if max_beam_width > 1: @@ -1076,6 +1077,7 @@ def _create_kv_cache_manager( spec_config=spec_config, is_estimating_kv_cache=estimating_kv_cache, execution_stream=execution_stream, + model_type="qwen3_next", ) else: # NOTE: this is a workaround for VSWA to switch to calculate_max_num_blocks_for_vswa in KVCahceManager diff --git a/tensorrt_llm/_torch/pyexecutor/mamba_cache_manager.py b/tensorrt_llm/_torch/pyexecutor/mamba_cache_manager.py index 94a317b54bbf..375a3d350dbe 100644 --- a/tensorrt_llm/_torch/pyexecutor/mamba_cache_manager.py +++ b/tensorrt_llm/_torch/pyexecutor/mamba_cache_manager.py @@ -199,6 +199,7 @@ def __init__( ssm_cache_dtype: torch.dtype, layer_mask: Optional[List[bool]] = None, speculative_num_draft_tokens: Optional[int] = None, + model_type: str = "nemotron_hybrid", ) -> None: self.mamba_ssm_cache_dtype = ssm_cache_dtype @@ -223,8 +224,15 @@ def __init__( conv_dim = conv_dim // tp_size nheads = nheads // tp_size - # Per-section dims for conv_state: [x | B | C] - self.conv_section_dims = [d_inner_local, ng_ds_local, ng_ds_local] + # Per-section dims for conv_state. + # Qwen3-Next: [Q | K | V] = [ng*ds, ng*ds, d_inner] + # Nemotron_hybrid: [x | B | C] = [d_inner, ng*ds, ng*ds] + if model_type == "qwen3_next": + self.conv_section_dims = [ng_ds_local, ng_ds_local, d_inner_local] + elif model_type == "nemotron_hybrid": + self.conv_section_dims = [d_inner_local, ng_ds_local, ng_ds_local] + else: + raise ValueError(f"Unsupported model type: {model_type}") # conv and ssm states device device = torch.device("cuda") @@ -509,6 +517,7 @@ def __init__( layer_mask: Optional[List[bool]] = None, stream: Optional[torch.cuda.Stream] = None, speculative_num_draft_tokens: Optional[int] = None, + model_type: str = "nemotron_hybrid", ) -> None: max_num_sequences = max_batch_size * mapping.pp_size self._use_cpp = use_cpp_mamba_cache_manager() @@ -545,6 +554,7 @@ def __init__( ssm_cache_dtype=ssm_cache_dtype, layer_mask=layer_mask, speculative_num_draft_tokens=speculative_num_draft_tokens, + model_type=model_type, ) def get_max_resource_count(self) -> int: @@ -631,7 +641,6 @@ def __init__( mamba_layer_mask: List[bool], mamba_cache_dtype: torch.dtype, mamba_ssm_cache_dtype: torch.dtype, - # kv cache parameters kv_cache_config: KvCacheConfig, kv_cache_type: CacheTypeCpp, @@ -650,6 +659,7 @@ def __init__( spec_config: Optional["DecodingBaseConfig"] = None, is_estimating_kv_cache: bool = False, execution_stream: Optional[torch.cuda.Stream] = None, + model_type: str = "nemotron_hybrid", ) -> None: # mamba hybrid cache requires block reuse to be disabled in KV cache config @@ -671,8 +681,9 @@ def __init__( mamba_ssm_cache_dtype, mamba_layer_mask, execution_stream, - speculative_num_draft_tokens=spec_config.max_draft_len - if spec_config is not None else None, + speculative_num_draft_tokens=(spec_config.max_draft_len + if spec_config is not None else None), + model_type=model_type, ) # initialize kv cache manager diff --git a/tests/integration/defs/accuracy/test_disaggregated_serving.py b/tests/integration/defs/accuracy/test_disaggregated_serving.py index b431f3801cd7..e365d4ec0805 100644 --- a/tests/integration/defs/accuracy/test_disaggregated_serving.py +++ b/tests/integration/defs/accuracy/test_disaggregated_serving.py @@ -1872,8 +1872,10 @@ def _make_configs(self, backend: str, use_python_runtime: bool = False): return ctx_server_config, gen_server_config, disaggregated_server_config @pytest.mark.skip_less_device(8) - def test_auto_dtype(self): - ctx_cfg, gen_cfg, disagg_cfg = self._make_configs("UCX") + @parametrize_with_ids("use_py_transceiver", [True, False]) + def test_auto_dtype(self, use_py_transceiver): + ctx_cfg, gen_cfg, disagg_cfg = self._make_configs( + "UCX", use_py_transceiver) with launch_disaggregated_llm(disagg_cfg, ctx_cfg, gen_cfg, self.MODEL_PATH) as llm: run_accuracy_test(llm, self.MODEL_NAME, ["GSM8K"]) @@ -1898,3 +1900,85 @@ def test_ctx_dp2_gen_tp4(self): with launch_disaggregated_llm(disagg_cfg, ctx_cfg, gen_cfg, self.MODEL_PATH) as llm: run_accuracy_test(llm, self.MODEL_NAME, ["GSM8K"]) + + +@pytest.mark.timeout(DEFAULT_TEST_TIMEOUT) +@skip_pre_blackwell +@pytest.mark.skip_less_device_memory(80000) +class TestQwen3NextInstruct(LlmapiAccuracyTestHarness): + MODEL_NAME = "Qwen3/Qwen3-Next-80B-A3B-Instruct" + MODEL_PATH = f"{llm_models_root()}/Qwen3-Next/Qwen3-Next-80B-A3B-Instruct" + + def _make_configs(self, use_py_transceiver: bool): + if use_py_transceiver: + cache_transceiver_config = { + "backend": "NIXL", + "max_tokens_in_buffer": 8192, + "transceiver_runtime": "PYTHON", + } + else: + cache_transceiver_config = { + "backend": "NIXL", + "max_tokens_in_buffer": 8192, + } + + ctx_server_config = { + "max_batch_size": 32, + "disable_overlap_scheduler": True, + "cache_transceiver_config": cache_transceiver_config, + "tensor_parallel_size": 4, + "moe_expert_parallel_size": 4, + "kv_cache_config": { + "enable_block_reuse": False, + "mamba_ssm_cache_dtype": "float16", + "free_gpu_memory_fraction": 0.5, + }, + "moe_config": { + "backend": "CUTLASS" + } + } + + gen_server_config = { + "max_batch_size": 32, + "disable_overlap_scheduler": False, + "cache_transceiver_config": cache_transceiver_config, + "tensor_parallel_size": 2, + "moe_expert_parallel_size": 2, + "pipeline_parallel_size": 2, + "cuda_graph_config": { + "max_batch_size": 32, + "enable_padding": True, + }, + "kv_cache_config": { + "enable_block_reuse": False, + "mamba_ssm_cache_dtype": "float16", + "free_gpu_memory_fraction": 0.5, + }, + "moe_config": { + "backend": "CUTLASS" + } + } + + disaggregated_server_config = { + "hostname": "localhost", + "port": 8000, + "backend": "pytorch", + "context_servers": { + "num_instances": 1, + "urls": ["localhost:8001"] + }, + "generation_servers": { + "num_instances": 1, + "urls": ["localhost:8002"] + } + } + return ctx_server_config, gen_server_config, disaggregated_server_config + + @pytest.mark.skip_less_device(8) + @parametrize_with_ids("use_py_transceiver", [True, False]) + def test_auto_dtype(self, use_py_transceiver, mocker): + mocker.patch.object(GSM8K, "MAX_OUTPUT_LEN", 512) + ctx_cfg, gen_cfg, disagg_cfg = self._make_configs(use_py_transceiver) + with launch_disaggregated_llm(disagg_cfg, ctx_cfg, gen_cfg, + self.MODEL_PATH) as llm: + run_accuracy_test(llm, self.MODEL_NAME, ["GSM8K"]) diff --git a/tests/integration/defs/accuracy/test_llm_api_pytorch.py b/tests/integration/defs/accuracy/test_llm_api_pytorch.py index 2f2ad63ab44e..f7cbdd219a14 100644 --- a/tests/integration/defs/accuracy/test_llm_api_pytorch.py +++ b/tests/integration/defs/accuracy/test_llm_api_pytorch.py @@ -5777,18 +5777,22 @@ class TestQwen3_5_397B_A17B(LlmapiAccuracyTestHarness): @pytest.mark.skip_less_device(4) @pytest.mark.parametrize( - "tp_size,ep_size,cuda_graph,overlap_scheduler,attention_dp", + "tp_size,ep_size,cuda_graph,overlap_scheduler,attention_dp, moe_backend", [ - (4, 4, True, True, False), - (4, 4, True, True, True), + (4, 4, True, True, False, "CUTEDSL"), + (4, 4, True, True, True, "CUTEDSL"), + (4, 4, True, True, False, "TRTLLM"), + (4, 4, True, True, True, "TRTLLM"), ], ids=[ - "tep4", - "adp4", + "tep4_cutedsl", + "adp4_cutedsl", + "tep4_trtllm", + "adp4_trtllm", ], ) def test_nvfp4(self, tp_size, ep_size, cuda_graph, overlap_scheduler, - attention_dp, mocker): + attention_dp, moe_backend, mocker): model_path = f"{llm_models_root()}/Qwen3.5-397B-A17B-NVFP4" if not os.path.exists(model_path): @@ -5807,7 +5811,7 @@ def test_nvfp4(self, tp_size, ep_size, cuda_graph, overlap_scheduler, max_batch_size=32, moe_expert_parallel_size=ep_size, kv_cache_config=kv_cache_config, - moe_config=MoeConfig(backend='TRTLLM'), + moe_config=MoeConfig(backend=moe_backend), enable_attention_dp=attention_dp, **pytorch_config) as llm: assert llm.args.quant_config.quant_algo == QuantAlgo.NVFP4 diff --git a/tests/integration/defs/disaggregated/test_configs/disagg_config_ctxtp2ep2pp2_gentp4_deepseek_v3_lite_one_mtp_block_reuse_chunked.yaml b/tests/integration/defs/disaggregated/test_configs/disagg_config_ctxtp2ep2pp2_gentp4_deepseek_v3_lite_one_mtp_block_reuse_chunked.yaml new file mode 100644 index 000000000000..ee58fbfd55a7 --- /dev/null +++ b/tests/integration/defs/disaggregated/test_configs/disagg_config_ctxtp2ep2pp2_gentp4_deepseek_v3_lite_one_mtp_block_reuse_chunked.yaml @@ -0,0 +1,34 @@ +hostname: localhost +model: DeepSeek-V3-Lite/fp8 +free_gpu_memory_fraction: 0.1 +backend: pytorch +cuda_graph_config: null +context_servers: + num_instances: 1 + tensor_parallel_size: 2 + pipeline_parallel_size: 2 + moe_expert_parallel_size: 2 + enable_attention_dp: true + disable_overlap_scheduler: true + max_num_tokens: 256 + enable_chunked_prefill: true + speculative_config: + decoding_type: MTP + num_nextn_predict_layers: 1 + kv_cache_config: + enable_block_reuse: true + cache_transceiver_config: + backend: DEFAULT +generation_servers: + num_instances: 1 + tensor_parallel_size: 4 + pipeline_parallel_size: 1 + moe_expert_parallel_size: 4 + enable_attention_dp: true + speculative_config: + decoding_type: MTP + num_nextn_predict_layers: 1 + kv_cache_config: + enable_block_reuse: true + cache_transceiver_config: + backend: DEFAULT diff --git a/tests/integration/defs/disaggregated/test_disaggregated.py b/tests/integration/defs/disaggregated/test_disaggregated.py index 1c8072b02412..b5d08a224fb7 100644 --- a/tests/integration/defs/disaggregated/test_disaggregated.py +++ b/tests/integration/defs/disaggregated/test_disaggregated.py @@ -235,6 +235,8 @@ def get_test_config(test_desc, example_dir, test_root): f"{test_configs_root}/disagg_config_ctxtp1_gentp1_deepseek_v3_lite_one_mtp_ctxpp2_gentp2.yaml", "deepseek_v3_lite_fp8_ctxtp2ep2pp2_gentp4_one_mtp_block_reuse": f"{test_configs_root}/disagg_config_ctxtp2ep2pp2_gentp4_deepseek_v3_lite_one_mtp_block_reuse.yaml", + "deepseek_v3_lite_fp8_ctxtp2ep2pp2_gentp4_one_mtp_block_reuse_chunked": + f"{test_configs_root}/disagg_config_ctxtp2ep2pp2_gentp4_deepseek_v3_lite_one_mtp_block_reuse_chunked.yaml", "deepseek_v3_lite_bf16_empty_batch": f"{test_configs_root}/disagg_config_deepseek_v3_lite_empty_batch.yaml", "llama4_kv_cache_overflow": @@ -1228,6 +1230,28 @@ def test_disaggregated_deepseek_v3_lite_fp8_ctxtp2ep2pp2_gentp4_one_mtp_block_re cwd=llm_venv.get_working_directory()) +@pytest.mark.skip_less_device(8) +@skip_no_hopper +@pytest.mark.parametrize("deepseek_v3_model_root", ['DeepSeek-V3-Lite-fp8'], + indirect=True) +def test_disaggregated_deepseek_v3_lite_fp8_ctxtp2ep2pp2_gentp4_one_mtp_block_reuse_long_prompt( + disaggregated_test_root, disaggregated_example_root, llm_venv, + deepseek_v3_model_root): + # NVBug 5991576: repeated long prompts with PP+disagg+block_reuse + # trigger scheduler hang due to reusable token budget miscalculation. + setup_model_symlink(llm_venv, deepseek_v3_model_root, + "DeepSeek-V3-Lite/fp8") + + run_disaggregated_test( + disaggregated_example_root, + "deepseek_v3_lite_fp8_ctxtp2ep2pp2_gentp4_one_mtp_block_reuse_chunked", + num_iters=5, + prompt_file="long_prompts.json", + env=llm_venv._new_env, + model_path=deepseek_v3_model_root, + cwd=llm_venv.get_working_directory()) + + @skip_no_hopper @skip_arm @pytest.mark.skip_less_device(4) diff --git a/tests/integration/test_lists/qa/llm_function_core.txt b/tests/integration/test_lists/qa/llm_function_core.txt index ec5af206555b..a49644bbb479 100644 --- a/tests/integration/test_lists/qa/llm_function_core.txt +++ b/tests/integration/test_lists/qa/llm_function_core.txt @@ -334,6 +334,10 @@ accuracy/test_llm_api_pytorch.py::TestNemotronV3Super::test_nvfp4_parallelism[TP accuracy/test_llm_api_pytorch.py::TestNemotronV3Super::test_nvfp4_parallelism[TEP8_PP1] accuracy/test_llm_api_pytorch.py::TestNemotronV3Super::test_nvfp4_parallelism[TP8_PP1_ADP] accuracy/test_llm_api_pytorch.py::TestGLM5FP8::test_8gpus[tp_size=8-ep_size=8] +accuracy/test_llm_api_pytorch.py::TestQwen3_5_397B_A17B::test_nvfp4[adp4_cutedsl] +accuracy/test_llm_api_pytorch.py::TestQwen3_5_397B_A17B::test_nvfp4[adp4_trtllm] +accuracy/test_llm_api_pytorch.py::TestQwen3_5_397B_A17B::test_nvfp4[tep4_cutedsl] +accuracy/test_llm_api_pytorch.py::TestQwen3_5_397B_A17B::test_nvfp4[tep4_trtllm] # multimodal accuracy tests accuracy/test_llm_api_pytorch_multimodal.py::TestQwen2_VL_7B::test_auto_dtype @@ -424,8 +428,12 @@ accuracy/test_disaggregated_serving.py::TestQwen3_8B::test_auto_dtype[True-True] accuracy/test_disaggregated_serving.py::TestQwen3_8B::test_auto_dtype[False-False] accuracy/test_disaggregated_serving.py::TestQwen3_8B::test_nixl_backend accuracy/test_disaggregated_serving.py::TestKimiK2::test_nvfp4 -accuracy/test_disaggregated_serving.py::TestNemotron3Super120B::test_auto_dtype +accuracy/test_disaggregated_serving.py::TestNemotron3Super120B::test_auto_dtype[use_py_transceiver=True] +accuracy/test_disaggregated_serving.py::TestNemotron3Super120B::test_auto_dtype[use_py_transceiver=False] accuracy/test_disaggregated_serving.py::TestNemotron3Super120B::test_nixl_backend +accuracy/test_disaggregated_serving.py::TestNemotron3Super120B::test_ctx_dp2_gen_tp4 +accuracy/test_disaggregated_serving.py::TestQwen3NextInstruct::test_auto_dtype[use_py_transceiver=True] +accuracy/test_disaggregated_serving.py::TestQwen3NextInstruct::test_auto_dtype[use_py_transceiver=False] # e2e test test_e2e.py::test_llama_e2e[use_py_session-remove_input_padding-] @@ -521,6 +529,7 @@ disaggregated/test_disaggregated.py::test_disaggregated_deepseek_v3_lite_fp8_att disaggregated/test_disaggregated.py::test_disaggregated_deepseek_v3_lite_fp8_attention_dp_gen_only[DeepSeek-V3-Lite-fp8] disaggregated/test_disaggregated.py::test_disaggregated_load_balance[TinyLlama-1.1B-Chat-v1.0] disaggregated/test_disaggregated.py::test_disaggregated_cache_aware_balance[TinyLlama-1.1B-Chat-v1.0] +disaggregated/test_disaggregated.py::test_disaggregated_deepseek_v3_lite_fp8_ctxtp2ep2pp2_gentp4_one_mtp_block_reuse_long_prompt[DeepSeek-V3-Lite-fp8] disaggregated/test_disaggregated.py::test_disaggregated_trtllm_sampler[TinyLlama-1.1B-Chat-v1.0] disaggregated/test_disaggregated.py::test_llama4_long_context_kv_cache_overflow[llama4-models/nvidia/Llama-4-Maverick-17B-128E-Instruct-FP8] disaggregated/test_disaggregated_single_gpu.py::test_disaggregated_simple_qwen3[False-False-Qwen3-8B-FP8] diff --git a/tests/integration/test_lists/test-db/l0_dgx_b200.yml b/tests/integration/test_lists/test-db/l0_dgx_b200.yml index 067ee4cee717..8b2459b3ca46 100644 --- a/tests/integration/test_lists/test-db/l0_dgx_b200.yml +++ b/tests/integration/test_lists/test-db/l0_dgx_b200.yml @@ -19,8 +19,8 @@ l0_dgx_b200: - accuracy/test_llm_api_pytorch.py::TestNemotronV3Super::test_auto_dtype_4gpus[4-4-False-True-True] - accuracy/test_llm_api_pytorch.py::TestNemotronV3Super::test_auto_dtype_4gpus[4-4-True-True-True] - accuracy/test_llm_api_pytorch.py::TestNemotronV3Super::test_nvfp4_4gpu_mtp_ar TIMEOUT (60) - - accuracy/test_llm_api_pytorch.py::TestQwen3_5_397B_A17B::test_nvfp4[adp4] - - accuracy/test_llm_api_pytorch.py::TestQwen3_5_397B_A17B::test_nvfp4[tep4] + - accuracy/test_llm_api_pytorch.py::TestQwen3_5_397B_A17B::test_nvfp4[adp4_cutedsl] + - accuracy/test_llm_api_pytorch.py::TestQwen3_5_397B_A17B::test_nvfp4[adp4_trtllm] - accuracy/test_llm_api_pytorch.py::TestNemotronV3Super::test_nvfp4_4gpus_static_eplb[moe_backend=CUTLASS] - accuracy/test_llm_api_pytorch.py::TestNemotronV3Super::test_nvfp4_4gpus_static_eplb[moe_backend=TRTLLM] - accuracy/test_llm_api_pytorch.py::TestQwen3_30B_A3B::test_nvfp4[tep4_latency_moe_trtllm-torch_compile=True] @@ -148,8 +148,12 @@ l0_dgx_b200: - accuracy/test_llm_api_pytorch.py::TestNemotronV3Super::test_nvfp4_8gpus[attention_dp_on-cutlass] TIMEOUT (60) - accuracy/test_llm_api_pytorch.py::TestNemotronV3Super::test_nvfp4_parallelism[TP4_PP2] TIMEOUT (60) - accuracy/test_llm_api_pytorch.py::TestGLM5FP8::test_8gpus[tp_size=8-ep_size=8] TIMEOUT (60) - - accuracy/test_disaggregated_serving.py::TestNemotron3Super120B::test_auto_dtype TIMEOUT (60) + - accuracy/test_disaggregated_serving.py::TestNemotron3Super120B::test_auto_dtype[use_py_transceiver=True] TIMEOUT (60) + - accuracy/test_disaggregated_serving.py::TestNemotron3Super120B::test_auto_dtype[use_py_transceiver=False] TIMEOUT (60) - accuracy/test_disaggregated_serving.py::TestNemotron3Super120B::test_nixl_backend TIMEOUT (60) + - accuracy/test_disaggregated_serving.py::TestNemotron3Super120B::test_ctx_dp2_gen_tp4 TIMEOUT (60) + - accuracy/test_disaggregated_serving.py::TestQwen3NextInstruct::test_auto_dtype[use_py_transceiver=True] TIMEOUT (60) + - accuracy/test_disaggregated_serving.py::TestQwen3NextInstruct::test_auto_dtype[use_py_transceiver=False] TIMEOUT (60) - condition: ranges: system_gpu_count: @@ -244,6 +248,8 @@ l0_dgx_b200: - accuracy/test_llm_api_pytorch.py::TestQwen3_30B_A3B::test_nvfp4[tep4_latency_moe_cutlass-torch_compile=False] - accuracy/test_llm_api_pytorch.py::TestQwen3_30B_A3B::test_nvfp4[tep4_latency_moe_cutlass-torch_compile=True] - accuracy/test_llm_api_pytorch.py::TestQwen3_30B_A3B::test_nvfp4[dep4_latency_moe_trtllm-torch_compile=True] + - accuracy/test_llm_api_pytorch.py::TestQwen3_5_397B_A17B::test_nvfp4[tep4_cutedsl] + - accuracy/test_llm_api_pytorch.py::TestQwen3_5_397B_A17B::test_nvfp4[tep4_trtllm] - accuracy/test_llm_api_pytorch.py::TestLlama4ScoutInstruct::test_fp8[tp4-cuda_graph=True] - accuracy/test_llm_api_pytorch.py::TestLlama4ScoutInstruct::test_auto_dtype[tp8-cuda_graph=False] - accuracy/test_llm_api_pytorch.py::TestLlama4ScoutInstruct::test_auto_dtype[tp8ep4-cuda_graph=True]