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xet

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danieldk HF Staff commited on Jun 18

Commit

357874b

1 Parent(s): 2fa7dc3

Remove builds incompatible with kernels >= 0.14

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Files changed (12) hide show

build/torch29-cxx11-cu129-aarch64-linux/__init__.py +0 -26
build/torch29-cxx11-cu129-aarch64-linux/_layer_norm_cuda_abf7d7d.abi3.so +0 -3
build/torch29-cxx11-cu129-aarch64-linux/_ops.py +0 -9
build/torch29-cxx11-cu129-aarch64-linux/layer_norm/__init__.py +0 -26
build/torch29-cxx11-cu129-aarch64-linux/layers.py +0 -51
build/torch29-cxx11-cu129-aarch64-linux/metadata.json +0 -15
build/torch29-cxx11-cu129-x86_64-linux/__init__.py +0 -26
build/torch29-cxx11-cu129-x86_64-linux/_layer_norm_cuda_abf7d7d.abi3.so +0 -3
build/torch29-cxx11-cu129-x86_64-linux/_ops.py +0 -9
build/torch29-cxx11-cu129-x86_64-linux/layer_norm/__init__.py +0 -26
build/torch29-cxx11-cu129-x86_64-linux/layers.py +0 -51
build/torch29-cxx11-cu129-x86_64-linux/metadata.json +0 -15

build/torch29-cxx11-cu129-aarch64-linux/__init__.py DELETED Viewed

@@ -1,26 +0,0 @@
-import torch
-import torch.nn as nn
-from ._ops import ops
-from . import layers
-def dropout_add_ln_fwd(input, gamma, beta, rowscale, colscale, x0_subset, z_subset, dropout_p, epsilon, rowscale_const, z_numrows, gen, residual_in_fp32, is_rms_norm):
-    return ops.dropout_add_ln_fwd(input, gamma, beta, rowscale, colscale, x0_subset, z_subset, dropout_p, epsilon, rowscale_const, z_numrows, gen, residual_in_fp32, is_rms_norm)
-def dropout_add_ln_bwd(dz, dx, x, mu, rsigma, gamma, rowscale, colscale, x0_subset, z_subset, dropout_p, rowscale_const, x0_numrows, has_residual, is_rms_norm):
-    return ops.dropout_add_ln_bwd(dz, dx, x, mu, rsigma, gamma, rowscale, colscale, x0_subset, z_subset, dropout_p, rowscale_const, x0_numrows, has_residual, is_rms_norm)
-def dropout_add_ln_parallel_residual_fwd(input, gamma0, beta0, gamma1, beta1, dropout_p, epsilon, gen, residual_in_fp32, is_rms_norm):
-    return ops.dropout_add_ln_parallel_residual_fwd(input, gamma0, beta0, gamma1, beta1, dropout_p, epsilon, gen, residual_in_fp32, is_rms_norm)
-def dropout_add_ln_parallel_residual_bwd(dz0, dz1, dx, x, mu, rsigma, gamma0, gamma1, dropout_p, has_x1, has_residual, is_rms_norm):
-    return ops.dropout_add_ln_parallel_residual_bwd(dz0, dz1, dx, x, mu, rsigma, gamma0, gamma1, dropout_p, has_x1, has_residual, is_rms_norm)
-__all__ = [
-    "layers",
-    "dropout_add_ln_fwd",
-    "dropout_add_ln_bwd",
-    "dropout_add_ln_parallel_residual_fwd",
-    "dropout_add_ln_parallel_residual_bwd",
-]

build/torch29-cxx11-cu129-aarch64-linux/_layer_norm_cuda_abf7d7d.abi3.so DELETED Viewed

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:b8c9f84d3152ac716ccefc08e081e3c387156bc00b65eb003b1b6e7385bdc15d
-size 1282721000

build/torch29-cxx11-cu129-aarch64-linux/_ops.py DELETED Viewed

@@ -1,9 +0,0 @@
-import torch
-from . import _layer_norm_cuda_abf7d7d
-ops = torch.ops._layer_norm_cuda_abf7d7d
-def add_op_namespace_prefix(op_name: str):
-    """
-    Prefix op by namespace.
-    """
-    return f"_layer_norm_cuda_abf7d7d::{op_name}"

build/torch29-cxx11-cu129-aarch64-linux/layer_norm/__init__.py DELETED Viewed

@@ -1,26 +0,0 @@
-import ctypes
-import importlib.util
-import sys
-from pathlib import Path
-from types import ModuleType
-def _import_from_path(file_path: Path) -> ModuleType:
-    # We cannot use the module name as-is, after adding it to `sys.modules`,
-    # it would also be used for other imports. So, we make a module name that
-    # depends on the path for it to be unique using the hex-encoded hash of
-    # the path.
-    path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
-    module_name = path_hash
-    spec = importlib.util.spec_from_file_location(module_name, file_path)
-    if spec is None:
-        raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
-    module = importlib.util.module_from_spec(spec)
-    if module is None:
-        raise ImportError(f"Cannot load module {module_name} from spec")
-    sys.modules[module_name] = module
-    spec.loader.exec_module(module)  # type: ignore
-    return module
-globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))

build/torch29-cxx11-cu129-aarch64-linux/layers.py DELETED Viewed

@@ -1,51 +0,0 @@
-import torch
-import torch.nn as nn
-from ._ops import ops
-class LayerNorm(nn.Module):
-    weight: torch.Tensor
-    variance_epsilon: float
-    def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
-        output = ops.dropout_add_ln_fwd(
-            hidden_states.view(-1, hidden_states.shape[-1]),
-            gamma = self.weight,
-            beta = None,
-            rowscale = None,
-            colscale = None,
-            x0_subset = None,
-            z_subset = None,
-            dropout_p = 0,
-            epsilon = self.variance_epsilon,
-            rowscale_const = 1.0,
-            z_numrows = hidden_states.shape[1],
-            gen = None,
-            residual_in_fp32 = False,
-            is_rms_norm = False,
-        )
-        return output[0].view(hidden_states.shape)
-class LlamaRMSNorm(nn.Module):
-    weight: torch.Tensor
-    variance_epsilon: float
-    def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
-        output = ops.dropout_add_ln_fwd(
-            hidden_states.view(-1, hidden_states.shape[-1]),
-            gamma = self.weight,
-            beta = None,
-            rowscale = None,
-            colscale = None,
-            x0_subset = None,
-            z_subset = None,
-            dropout_p = 0,
-            epsilon = self.variance_epsilon,
-            rowscale_const = 1.0,
-            z_numrows = hidden_states.shape[1],
-            gen = None,
-            residual_in_fp32 = False,
-            is_rms_norm = True,
-        )
-        return output[0].view(hidden_states.shape)

build/torch29-cxx11-cu129-aarch64-linux/metadata.json DELETED Viewed

@@ -1,15 +0,0 @@
-{
-  "version": 1,
-  "license": "BSD-3-Clause",
-  "python-depends": [],
-  "backend": {
-    "type": "cuda",
-    "archs": [
-      "10.0",
-      "12.0",
-      "8.0",
-      "8.9",
-      "9.0"
-    ]
-  }
-}

build/torch29-cxx11-cu129-x86_64-linux/__init__.py DELETED Viewed

@@ -1,26 +0,0 @@
-import torch
-import torch.nn as nn
-from ._ops import ops
-from . import layers
-def dropout_add_ln_fwd(input, gamma, beta, rowscale, colscale, x0_subset, z_subset, dropout_p, epsilon, rowscale_const, z_numrows, gen, residual_in_fp32, is_rms_norm):
-    return ops.dropout_add_ln_fwd(input, gamma, beta, rowscale, colscale, x0_subset, z_subset, dropout_p, epsilon, rowscale_const, z_numrows, gen, residual_in_fp32, is_rms_norm)
-def dropout_add_ln_bwd(dz, dx, x, mu, rsigma, gamma, rowscale, colscale, x0_subset, z_subset, dropout_p, rowscale_const, x0_numrows, has_residual, is_rms_norm):
-    return ops.dropout_add_ln_bwd(dz, dx, x, mu, rsigma, gamma, rowscale, colscale, x0_subset, z_subset, dropout_p, rowscale_const, x0_numrows, has_residual, is_rms_norm)
-def dropout_add_ln_parallel_residual_fwd(input, gamma0, beta0, gamma1, beta1, dropout_p, epsilon, gen, residual_in_fp32, is_rms_norm):
-    return ops.dropout_add_ln_parallel_residual_fwd(input, gamma0, beta0, gamma1, beta1, dropout_p, epsilon, gen, residual_in_fp32, is_rms_norm)
-def dropout_add_ln_parallel_residual_bwd(dz0, dz1, dx, x, mu, rsigma, gamma0, gamma1, dropout_p, has_x1, has_residual, is_rms_norm):
-    return ops.dropout_add_ln_parallel_residual_bwd(dz0, dz1, dx, x, mu, rsigma, gamma0, gamma1, dropout_p, has_x1, has_residual, is_rms_norm)
-__all__ = [
-    "layers",
-    "dropout_add_ln_fwd",
-    "dropout_add_ln_bwd",
-    "dropout_add_ln_parallel_residual_fwd",
-    "dropout_add_ln_parallel_residual_bwd",
-]

build/torch29-cxx11-cu129-x86_64-linux/_layer_norm_cuda_abf7d7d.abi3.so DELETED Viewed

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:91f86328f0302dd6ec2d76a1ba8a70bc9c4daa3d9d3739d650fd124b11fdf49a
-size 1283022120

build/torch29-cxx11-cu129-x86_64-linux/_ops.py DELETED Viewed

@@ -1,9 +0,0 @@
-import torch
-from . import _layer_norm_cuda_abf7d7d
-ops = torch.ops._layer_norm_cuda_abf7d7d
-def add_op_namespace_prefix(op_name: str):
-    """
-    Prefix op by namespace.
-    """
-    return f"_layer_norm_cuda_abf7d7d::{op_name}"

build/torch29-cxx11-cu129-x86_64-linux/layer_norm/__init__.py DELETED Viewed

@@ -1,26 +0,0 @@
-import ctypes
-import importlib.util
-import sys
-from pathlib import Path
-from types import ModuleType
-def _import_from_path(file_path: Path) -> ModuleType:
-    # We cannot use the module name as-is, after adding it to `sys.modules`,
-    # it would also be used for other imports. So, we make a module name that
-    # depends on the path for it to be unique using the hex-encoded hash of
-    # the path.
-    path_hash = "{:x}".format(ctypes.c_size_t(hash(file_path.absolute())).value)
-    module_name = path_hash
-    spec = importlib.util.spec_from_file_location(module_name, file_path)
-    if spec is None:
-        raise ImportError(f"Cannot load spec for {module_name} from {file_path}")
-    module = importlib.util.module_from_spec(spec)
-    if module is None:
-        raise ImportError(f"Cannot load module {module_name} from spec")
-    sys.modules[module_name] = module
-    spec.loader.exec_module(module)  # type: ignore
-    return module
-globals().update(vars(_import_from_path(Path(__file__).parent.parent / "__init__.py")))

build/torch29-cxx11-cu129-x86_64-linux/layers.py DELETED Viewed

@@ -1,51 +0,0 @@
-import torch
-import torch.nn as nn
-from ._ops import ops
-class LayerNorm(nn.Module):
-    weight: torch.Tensor
-    variance_epsilon: float
-    def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
-        output = ops.dropout_add_ln_fwd(
-            hidden_states.view(-1, hidden_states.shape[-1]),
-            gamma = self.weight,
-            beta = None,
-            rowscale = None,
-            colscale = None,
-            x0_subset = None,
-            z_subset = None,
-            dropout_p = 0,
-            epsilon = self.variance_epsilon,
-            rowscale_const = 1.0,
-            z_numrows = hidden_states.shape[1],
-            gen = None,
-            residual_in_fp32 = False,
-            is_rms_norm = False,
-        )
-        return output[0].view(hidden_states.shape)
-class LlamaRMSNorm(nn.Module):
-    weight: torch.Tensor
-    variance_epsilon: float
-    def forward(self, hidden_states: torch.Tensor) -> torch.Tensor:
-        output = ops.dropout_add_ln_fwd(
-            hidden_states.view(-1, hidden_states.shape[-1]),
-            gamma = self.weight,
-            beta = None,
-            rowscale = None,
-            colscale = None,
-            x0_subset = None,
-            z_subset = None,
-            dropout_p = 0,
-            epsilon = self.variance_epsilon,
-            rowscale_const = 1.0,
-            z_numrows = hidden_states.shape[1],
-            gen = None,
-            residual_in_fp32 = False,
-            is_rms_norm = True,
-        )
-        return output[0].view(hidden_states.shape)

build/torch29-cxx11-cu129-x86_64-linux/metadata.json DELETED Viewed

@@ -1,15 +0,0 @@
-{
-  "version": 1,
-  "license": "BSD-3-Clause",
-  "python-depends": [],
-  "backend": {
-    "type": "cuda",
-    "archs": [
-      "10.0",
-      "12.0",
-      "8.0",
-      "8.9",
-      "9.0"
-    ]
-  }
-}