feat: Updated torch version mapping form 2.1.2 to 2.2 (#28236)

ivy-llc · Feb 10, 2024 · 3277232 · 3277232
1 parent 1603886
commit 3277232
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Showing 51 changed files with 674 additions and 678 deletions.
diff --git a/ivy/functional/backends/torch/__init__.py b/ivy/functional/backends/torch/__init__.py
@@ -129,7 +129,7 @@ def rep_method(*args, **kwargs):
 
 # update these to add new dtypes
 valid_dtypes = {
-    "2.1.2 and below": (
+    "2.2 and below": (
         ivy.int8,
         ivy.int16,
         ivy.int32,
@@ -147,7 +147,7 @@ def rep_method(*args, **kwargs):
 
 
 valid_numeric_dtypes = {
-    "2.1.2 and below": (
+    "2.2 and below": (
         ivy.int8,
         ivy.int16,
         ivy.int32,
@@ -163,13 +163,13 @@ def rep_method(*args, **kwargs):
 }
 
 valid_int_dtypes = {
-    "2.1.2 and below": (ivy.int8, ivy.int16, ivy.int32, ivy.int64, ivy.uint8)
+    "2.2 and below": (ivy.int8, ivy.int16, ivy.int32, ivy.int64, ivy.uint8)
 }
 valid_float_dtypes = {
-    "2.1.2 and below": (ivy.bfloat16, ivy.float16, ivy.float32, ivy.float64)
+    "2.2 and below": (ivy.bfloat16, ivy.float16, ivy.float32, ivy.float64)
 }
-valid_uint_dtypes = {"2.1.2 and below": (ivy.uint8,)}
-valid_complex_dtypes = {"2.1.2 and below": (ivy.complex64, ivy.complex128)}
+valid_uint_dtypes = {"2.2 and below": (ivy.uint8,)}
+valid_complex_dtypes = {"2.2 and below": (ivy.complex64, ivy.complex128)}
 
 # leave these untouched
 valid_dtypes = _dtype_from_version(valid_dtypes, backend_version)
@@ -182,17 +182,17 @@ def rep_method(*args, **kwargs):
 # invalid data types
 # update these to add new dtypes
 invalid_dtypes = {
-    "2.1.2 and below": (
+    "2.2 and below": (
         ivy.uint16,
         ivy.uint32,
         ivy.uint64,
     )
 }
-invalid_numeric_dtypes = {"2.1.2 and below": (ivy.uint16, ivy.uint32, ivy.uint64)}
-invalid_int_dtypes = {"2.1.2 and below": (ivy.uint16, ivy.uint32, ivy.uint64)}
-invalid_float_dtypes = {"2.1.2 and below": ()}
-invalid_uint_dtypes = {"2.1.2 and below": (ivy.uint16, ivy.uint32, ivy.uint64)}
-invalid_complex_dtypes = {"2.1.2 and below": ()}
+invalid_numeric_dtypes = {"2.2 and below": (ivy.uint16, ivy.uint32, ivy.uint64)}
+invalid_int_dtypes = {"2.2 and below": (ivy.uint16, ivy.uint32, ivy.uint64)}
+invalid_float_dtypes = {"2.2 and below": ()}
+invalid_uint_dtypes = {"2.2 and below": (ivy.uint16, ivy.uint32, ivy.uint64)}
+invalid_complex_dtypes = {"2.2 and below": ()}
 invalid_dtypes = _dtype_from_version(invalid_dtypes, backend_version)
 
 # leave these untouched

diff --git a/ivy/functional/backends/torch/activations.py b/ivy/functional/backends/torch/activations.py
@@ -18,14 +18,14 @@
 import ivy.functional.backends.torch as torch_backend
 
 
-@with_unsupported_dtypes({"2.1.2 and below": ("float16",)}, backend_version)
+@with_unsupported_dtypes({"2.2 and below": ("float16",)}, backend_version)
 def relu(
     x: torch.Tensor, /, *, complex_mode="jax", out: Optional[torch.Tensor] = None
 ) -> torch.Tensor:
     return torch.relu(x)
 
 
-@with_unsupported_dtypes({"2.1.2 and below": ("float16",)}, backend_version)
+@with_unsupported_dtypes({"2.2 and below": ("float16",)}, backend_version)
 def leaky_relu(
     x: torch.Tensor,
     /,
@@ -37,7 +37,7 @@ def leaky_relu(
     return torch.nn.functional.leaky_relu(x, alpha)
 
 
-@with_unsupported_dtypes({"2.1.2 and below": ("float16",)}, backend_version)
+@with_unsupported_dtypes({"2.2 and below": ("float16",)}, backend_version)
 def gelu(
     x: torch.Tensor,
     /,
@@ -51,7 +51,7 @@ def gelu(
     return torch.nn.functional.gelu(x)
 
 
-@with_unsupported_dtypes({"2.1.2 and below": ("float16",)}, backend_version)
+@with_unsupported_dtypes({"2.2 and below": ("float16",)}, backend_version)
 def sigmoid(
     x: torch.Tensor, /, *, complex_mode="jax", out: Optional[torch.Tensor] = None
 ) -> torch.Tensor:
@@ -63,7 +63,7 @@ def sigmoid(
 sigmoid.support_native_out = True
 
 
-@with_unsupported_dtypes({"2.1.2 and below": ("bfloat16", "float16")}, backend_version)
+@with_unsupported_dtypes({"2.2 and below": ("bfloat16", "float16")}, backend_version)
 def softmax(
     x: torch.Tensor,
     /,
@@ -80,7 +80,7 @@ def softmax(
     return torch.nn.functional.softmax(x, axis)
 
 
-@with_unsupported_dtypes({"2.1.2 and below": ("float16", "bfloat16")}, backend_version)
+@with_unsupported_dtypes({"2.2 and below": ("float16", "bfloat16")}, backend_version)
 def softplus(
     x: torch.Tensor,
     /,
@@ -97,7 +97,7 @@ def softplus(
 
 
 # Softsign
-@with_unsupported_dtypes({"2.1.2 and below": ("float16", "bfloat16")}, backend_version)
+@with_unsupported_dtypes({"2.2 and below": ("float16", "bfloat16")}, backend_version)
 def softsign(x: torch.Tensor, /, out: Optional[torch.Tensor] = None) -> torch.Tensor:
     # return x / (1 + torch.abs(x))
     return torch.nn.functional.softsign(x)
@@ -107,7 +107,7 @@ def softsign(x: torch.Tensor, /, out: Optional[torch.Tensor] = None) -> torch.Te
 
 
 @with_unsupported_dtypes(
-    {"2.1.2 and below": ("float16",)},
+    {"2.2 and below": ("float16",)},
     backend_version,
 )
 def log_softmax(
@@ -128,7 +128,7 @@ def log_softmax(
 
 
 @with_unsupported_dtypes(
-    {"2.1.2 and below": ("float16",)},
+    {"2.2 and below": ("float16",)},
     backend_version,
 )
 def mish(
@@ -146,7 +146,7 @@ def mish(
 
 @with_unsupported_dtypes(
     {
-        "2.1.2 and below": (
+        "2.2 and below": (
             "complex",
             "float16",
         )

diff --git a/ivy/functional/backends/torch/creation.py b/ivy/functional/backends/torch/creation.py
@@ -47,7 +47,7 @@ def _differentiable_linspace(start, stop, num, *, device, dtype=None):
     return res
 
 
-@with_unsupported_dtypes({"2.1.2 and below": ("complex",)}, backend_version)
+@with_unsupported_dtypes({"2.2 and below": ("complex",)}, backend_version)
 def arange(
     start: float,
     /,
@@ -95,7 +95,7 @@ def _stack_tensors(x, dtype):
     return x
 
 
-@with_unsupported_dtypes({"2.1.2 and below": ("bfloat16",)}, backend_version)
+@with_unsupported_dtypes({"2.2 and below": ("bfloat16",)}, backend_version)
 @_asarray_to_native_arrays_and_back
 @_asarray_infer_device
 @_asarray_handle_nestable
@@ -166,7 +166,7 @@ def empty_like(
     return torch.empty_like(x, dtype=dtype, device=device)
 
 
-@with_unsupported_dtypes({"2.1.2 and below": ("bfloat16",)}, backend_version)
+@with_unsupported_dtypes({"2.2 and below": ("bfloat16",)}, backend_version)
 def eye(
     n_rows: int,
     n_cols: Optional[int] = None,
@@ -276,7 +276,7 @@ def _slice_at_axis(sl, axis):
 
 
 @with_unsupported_device_and_dtypes(
-    {"2.1.2 and below": {"cpu": ("float16",)}}, backend_version
+    {"2.2 and below": {"cpu": ("float16",)}}, backend_version
 )
 def linspace(
     start: Union[torch.Tensor, float],

diff --git a/ivy/functional/backends/torch/data_type.py b/ivy/functional/backends/torch/data_type.py
@@ -72,7 +72,7 @@ def smallest_normal(self):
 # -------------------#
 
 
-@with_unsupported_dtypes({"2.1.2 and below": ("bfloat16", "float16")}, backend_version)
+@with_unsupported_dtypes({"2.2 and below": ("bfloat16", "float16")}, backend_version)
 def astype(
     x: torch.Tensor,
     dtype: torch.dtype,
@@ -181,7 +181,7 @@ def as_ivy_dtype(
         )
 
 
-@with_unsupported_dtypes({"2.1.2 and below": ("uint16",)}, backend_version)
+@with_unsupported_dtypes({"2.2 and below": ("uint16",)}, backend_version)
 def as_native_dtype(
     dtype_in: Union[torch.dtype, str, bool, int, float, np.dtype],
 ) -> torch.dtype: