Initialisation du repository de Beta

venv/lib/python3.12/site-packages/ctranslate2/specs/common_spec.py

@@ -0,0 +1,66 @@
+import enum
+
+from ctranslate2.specs import model_spec
+
+
+# This enum should match the C++ equivalent in include/ctranslate2/ops/activation.h.
+class Activation(enum.IntEnum):
+    """Activation type."""
+
+    RELU = 0
+    GELUTanh = 1
+    SWISH = 2
+    GELU = 3
+    GELUSigmoid = 4
+    Tanh = 5
+    Sigmoid = 6
+
+
+# This enum should match the C++ equivalent in include/ctranslate2/layers/common.h.
+class EmbeddingsMerge(enum.IntEnum):
+    """Merge strategy for factors embeddings."""
+
+    CONCAT = 0
+    ADD = 1
+
+
+class Quantization(enum.IntEnum):
+    """Activation type."""
+
+    CT2 = 0
+    AWQ_GEMM = 1
+    AWQ_GEMV = 2
+
+
+class LayerNormSpec(model_spec.LayerSpec):
+    def __init__(self, rms_norm=False):
+        self.gamma = None
+        if not rms_norm:
+            self.beta = None
+        else:
+            self.layer_norm_use_residual = model_spec.OPTIONAL
+
+
+class LinearSpec(model_spec.LayerSpec):
+    def __init__(self):
+        self.weight = None
+        self.weight_scale = model_spec.OPTIONAL
+        self.weight_zero = model_spec.OPTIONAL
+        self.bias = model_spec.OPTIONAL
+
+    def has_bias(self):
+        return not isinstance(self.bias, str)
+
+
+class Conv1DSpec(model_spec.LayerSpec):
+    def __init__(self):
+        self.weight = None
+        self.weight_scale = model_spec.OPTIONAL
+        self.bias = model_spec.OPTIONAL
+
+
+class EmbeddingsSpec(model_spec.LayerSpec):
+    def __init__(self):
+        self.weight = None
+        self.weight_scale = model_spec.OPTIONAL
+        self.multiply_by_sqrt_depth = model_spec.OPTIONAL