internlm/SWE-Fixer-Train-110K huggingface dataset:
Repository: ivy-llc/ivy

Issue:
subtract_



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/torch/tensor.py b/ivy/functional/frontends/torch/tensor.py
--- a/ivy/functional/frontends/torch/tensor.py
+++ b/ivy/functional/frontends/torch/tensor.py
@@ -93,6 +93,11 @@ def add_(self, other, *, alpha=1):
         self._ivy_array = self.add(other, alpha=alpha).ivy_array
         return self
 
+    @with_unsupported_dtypes({"1.11.0 and below": ("bfloat16",)}, "torch")
+    def subtract_(self, other, *, alpha=1):
+        self._ivy_array = self.subtract(other, alpha=alpha).ivy_array
+        return self
+
     @with_unsupported_dtypes({"1.11.0 and below": ("float16",)}, "torch")
     def asin(self):
         return torch_frontend.asin(self._ivy_array)


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
@@ -3175,6 +3175,42 @@ def test_torch_instance_add_(
     )
 
 
+
+# subtract_
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="subtract_",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("numeric"),
+        num_arrays=2,
+    ),
+)
+def test_torch_instance_subtract_(
+        dtype_and_x,
+        frontend_method_data,
+        init_flags,
+        method_flags,
+        frontend,
+        on_device,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_method(
+        init_input_dtypes=[input_dtype[0]],
+        init_all_as_kwargs_np={
+            "data": x[0],
+        },
+        method_input_dtypes=input_dtype,
+        method_all_as_kwargs_np={
+            "other": x[1],
+        },
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+    )
+
 # arccos_
 @handle_frontend_method(
     class_tree=CLASS_TREE,
@@ -3207,8 +3243,6 @@ def test_torch_instance_arccos_(
         method_flags=method_flags,
         frontend=frontend,
         on_device=on_device,
-    )
-
 
 # arccos
 @handle_frontend_method(
Repository: ivy-llc/ivy

Issue:
FFT



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/tensorflow/raw_ops.py b/ivy/functional/frontends/tensorflow/raw_ops.py
--- a/ivy/functional/frontends/tensorflow/raw_ops.py
+++ b/ivy/functional/frontends/tensorflow/raw_ops.py
@@ -202,6 +202,11 @@ def FloorMod(*, x, y, name="FloorMod"):
     return ivy.remainder(x, y)
 
 
+@to_ivy_arrays_and_back
+def FFT(*, input, name="FFT"):
+    return ivy.astype(ivy.fft(input, -1), input.dtype)
+
+
 @to_ivy_arrays_and_back
 def Gather(*, params, indices, validate_indices=None, name="Gather"):
     return ivy.gather(params, indices, axis=0, batch_dims=0)


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py
--- a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py
@@ -1327,6 +1327,37 @@ def test_tensorflow_FloorMod(  # NOQA
     )
 
 
+# FFT
+@handle_frontend_test(
+    fn_tree="tensorflow.raw_ops.FFT",
+    dtype_and_x=helpers.dtype_and_values(
+        min_num_dims=1,
+        min_dim_size=2,
+        small_abs_safety_factor=3,
+        safety_factor_scale="log",
+        available_dtypes=helpers.get_dtypes("complex"),
+    ),
+    test_with_out=st.just(False),
+)
+def test_tensorflow_FFT(  # NOQA
+    *,
+    dtype_and_x,
+    frontend,
+    test_flags,
+    fn_tree,
+    on_device,
+):
+    dtype, x = dtype_and_x
+    helpers.test_frontend_function(
+        input_dtypes=dtype,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        input=x[0],
+    )
+
+
 # Exp
 @handle_frontend_test(
     fn_tree="tensorflow.raw_ops.Exp",
Repository: ivy-llc/ivy

Issue:
imag



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/tensorflow/math.py b/ivy/functional/frontends/tensorflow/math.py
--- a/ivy/functional/frontends/tensorflow/math.py
+++ b/ivy/functional/frontends/tensorflow/math.py
@@ -9,6 +9,15 @@
 )
 
 
+@with_supported_dtypes(
+    {"2.9.0 and below": ("float16", "float32", "float64", "complex64", "complex128")},
+    "tensorflow",
+)
+@to_ivy_arrays_and_back
+def imag(input, name=None):
+    return ivy.imag(input)
+
+
 @to_ivy_arrays_and_back
 def accumulate_n(inputs, input_type=None, shape=None, dtype=None, name=None):
     return ivy.astype(ivy.sum(ivy.array(inputs)), ivy.int64)


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_math.py b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_math.py
--- a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_math.py
+++ b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_math.py
@@ -11,6 +11,37 @@
 from ivy_tests.test_ivy.helpers import handle_frontend_test
 
 
+# imag
+@handle_frontend_test(
+    fn_tree="tensorflow.math.imag",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float_and_complex"),
+        min_value=-20,
+        max_value=20,
+    ),
+    test_with_out=st.just(False),
+)
+def test_tensorflow_imag(
+    *,
+    dtype_and_x,
+    test_flags,
+    on_device,
+    fn_tree,
+    frontend,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        test_flags=test_flags,
+        frontend=frontend,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        rtol=1e-2,
+        atol=1e-2,
+        input=x[0],
+    )
+
+
 # accumulate_n
 @handle_frontend_test(
     fn_tree="tensorflow.math.accumulate_n",
Repository: ivy-llc/ivy

Issue:
logical_not



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/tensorflow/math.py b/ivy/functional/frontends/tensorflow/math.py
--- a/ivy/functional/frontends/tensorflow/math.py
+++ b/ivy/functional/frontends/tensorflow/math.py
@@ -193,6 +193,11 @@ def log_sigmoid(x, name=None):
     return -ivy.softplus(-x)
 
 
+@to_ivy_arrays_and_back
+def logical_not(x, name="logical_not"):
+    return ivy.logical_not(x)
+  
+  
 @to_ivy_arrays_and_back
 def log1p(x, name=None):
     return ivy.log1p(x)


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_math.py b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_math.py
--- a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_math.py
+++ b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_math.py
@@ -321,6 +321,35 @@ def test_tensorflow_squared_difference(
     )
 
 
+# logical_not
+@handle_frontend_test(
+    fn_tree="tensorflow.math.logical_not",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=tuple([ivy.bool]),
+        num_arrays=2,
+        shared_dtype=True,
+    ),
+    test_with_out=st.just(False),
+)
+def test_tensorflow_logical_not(
+    *,
+    dtype_and_x,
+    frontend,
+    test_flags,
+    fn_tree,
+    on_device,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        x=x[0],
+    )
+
+
 # logical_xor
 @handle_frontend_test(
     fn_tree="tensorflow.math.logical_xor",
Repository: ivy-llc/ivy

Issue:
fix



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/torch/pointwise_ops.py b/ivy/functional/frontends/torch/pointwise_ops.py
--- a/ivy/functional/frontends/torch/pointwise_ops.py
+++ b/ivy/functional/frontends/torch/pointwise_ops.py
@@ -200,6 +200,9 @@ def trunc(input, *, out=None):
     return ivy.trunc(input, out=out)
 
 
+fix = trunc
+
+
 @with_unsupported_dtypes({"1.11.0 and below": ("float16",)}, "torch")
 @to_ivy_arrays_and_back
 def sqrt(input, *, out=None):


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_pointwise_ops.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_pointwise_ops.py
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_pointwise_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_pointwise_ops.py
@@ -890,6 +890,7 @@ def test_torch_log10(
 # trunc
 @handle_frontend_test(
     fn_tree="torch.trunc",
+    aliases=["torch.fix"],
     dtype_and_x=helpers.dtype_and_values(
         available_dtypes=helpers.get_dtypes("float"),
     ),
Repository: ivy-llc/ivy

Issue:
float_power



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/torch/pointwise_ops.py b/ivy/functional/frontends/torch/pointwise_ops.py
--- a/ivy/functional/frontends/torch/pointwise_ops.py
+++ b/ivy/functional/frontends/torch/pointwise_ops.py
@@ -361,6 +361,12 @@ def pow(input, exponent, *, out=None):
     return ivy.pow(input, exponent, out=out)
 
 
+@to_ivy_arrays_and_back
+def float_power(input, exponent, *, out=None):
+    input, exponent = torch_frontend.promote_types_of_torch_inputs(input, exponent)
+    return ivy.float_power(input, exponent, out=out)
+
+
 @to_ivy_arrays_and_back
 @with_unsupported_dtypes({"1.11.0 and below": ("float16",)}, "torch")
 def log(input, *, out=None):


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_pointwise_ops.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_pointwise_ops.py
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_pointwise_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_pointwise_ops.py
@@ -3,6 +3,7 @@
 from hypothesis import strategies as st, assume
 
 # local
+import ivy
 import ivy_tests.test_ivy.helpers as helpers
 from ivy_tests.test_ivy.helpers import handle_frontend_test
 
@@ -1651,6 +1652,60 @@ def test_torch_pow(
     )
 
 
+# float_power_helper
+@st.composite
+def _float_power_helper(draw, *, available_dtypes=None):
+    if available_dtypes is None:
+        available_dtypes = helpers.get_dtypes("numeric")
+    dtype1, x1 = draw(
+        helpers.dtype_and_values(
+            available_dtypes=available_dtypes,
+            small_abs_safety_factor=16,
+            large_abs_safety_factor=16,
+            safety_factor_scale="log",
+        )
+    )
+    dtype2 = draw(helpers.get_dtypes("numeric"))
+    if ivy.is_int_dtype(dtype2[0]):
+        min_value = 0
+    else:
+        min_value = -10
+    dtype2, x2 = draw(
+        helpers.dtype_and_values(
+            min_value=min_value,
+            max_value=10,
+            dtype=dtype2,
+        )
+    )
+    return (dtype1[0], dtype2[0]), (x1[0], x2[0])
+
+
+@handle_frontend_test(
+    fn_tree="torch.float_power",
+    dtype_and_x=_float_power_helper(),
+)
+def test_torch_float_power(
+    dtype_and_x,
+    on_device,
+    fn_tree,
+    frontend,
+    test_flags,
+):
+    input_dtype, x = dtype_and_x
+    # Making sure zero to the power of negative doesn't occur
+    assume(not np.any(np.isclose(x[0], 0)))
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        rtol=1e-03,
+        input=x[0],
+        exponent=x[1],
+    )
+
+
 # logaddexp
 @handle_frontend_test(
     fn_tree="torch.logaddexp",
Repository: ivy-llc/ivy

Issue:
frombuffer



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/torch/creation_ops.py b/ivy/functional/frontends/torch/creation_ops.py
--- a/ivy/functional/frontends/torch/creation_ops.py
+++ b/ivy/functional/frontends/torch/creation_ops.py
@@ -285,3 +285,15 @@ def asarray(
     copy=None,
 ):
     return ivy.asarray(obj, copy=copy, dtype=dtype, device=device)
+
+
+@to_ivy_arrays_and_back
+def frombuffer(
+    buffer, 
+    *, 
+    dtype,
+    count=-1,
+    offset=0,
+    requires_grad=False,
+):
+    return ivy.frombuffer(buffer, dtype=dtype, count=count, offset=offset)


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_creation_ops.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_creation_ops.py
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_creation_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_creation_ops.py
@@ -2,6 +2,7 @@
 import ivy
 from hypothesis import strategies as st, assume
 import math
+import numpy as np
 
 # local
 import ivy_tests.test_ivy.helpers as helpers
@@ -688,3 +689,48 @@ def test_torch_from_dlpack(
         fn_tree=fn_tree,
         on_device=on_device,
     )
+
+
+@st.composite
+def _get_dtype_buffer_count_offset(draw):
+    dtype, value = draw(
+        helpers.dtype_and_values(
+            available_dtypes=helpers.get_dtypes("valid"),
+        )
+    )
+    value = np.array(value)
+    length = value.size
+    value = value.tobytes()
+
+    offset = draw(helpers.ints(min_value=0, max_value=length - 1))
+    count = draw(helpers.ints(min_value=-(2**30), max_value=length - offset))
+    if count == 0:
+        count = -1
+    offset = offset * np.dtype(dtype[0]).itemsize
+
+    return dtype, value, count, offset
+
+
+@handle_frontend_test(
+    fn_tree="torch.frombuffer",
+    dtype_buffer_count_offset=_get_dtype_buffer_count_offset(),
+)
+def test_torch_frombuffer(
+    dtype_buffer_count_offset,
+    test_flags,
+    frontend,
+    fn_tree,
+    on_device,
+):
+    input_dtype, buffer, count, offset = dtype_buffer_count_offset
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        test_flags=test_flags,
+        on_device=on_device,
+        frontend=frontend,
+        fn_tree=fn_tree,
+        buffer=buffer,
+        dtype=input_dtype[0],
+        count=count,
+        offset=offset,
+    )
Repository: ivy-llc/ivy

Issue:
erf



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/torch/pointwise_ops.py b/ivy/functional/frontends/torch/pointwise_ops.py
--- a/ivy/functional/frontends/torch/pointwise_ops.py
+++ b/ivy/functional/frontends/torch/pointwise_ops.py
@@ -504,6 +504,12 @@ def logit(input, eps=None, *, out=None):
     return ivy.log(ivy.divide(input, ivy.subtract(1, input), out=out), out=out)
 
 
+@with_unsupported_dtypes({"1.11.0 and below": ("float16", "complex")}, "torch")
+@to_ivy_arrays_and_back
+def erf(input, *, out=None):
+    return ivy.erf(input, out=out)
+
+
 @to_ivy_arrays_and_back
 def sgn(input, *, out=None):
     if ivy.is_complex_dtype(input.dtype):


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_pointwise_ops.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_pointwise_ops.py
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_pointwise_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_pointwise_ops.py
@@ -2397,6 +2397,32 @@ def test_torch_logit(
     )
 
 
+# erf
+@handle_frontend_test(
+    fn_tree="torch.erf",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+    ),
+)
+def test_torch_erf(
+    *,
+    dtype_and_x,
+    on_device,
+    fn_tree,
+    frontend,
+    test_flags,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        input=x[0],
+    )
+
+
 @handle_frontend_test(
     fn_tree="torch.sgn",
     dtype_and_input=helpers.dtype_and_values(
Repository: ivy-llc/ivy

Issue:
log1p



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/tensorflow/math.py b/ivy/functional/frontends/tensorflow/math.py
--- a/ivy/functional/frontends/tensorflow/math.py
+++ b/ivy/functional/frontends/tensorflow/math.py
@@ -184,6 +184,11 @@ def log_sigmoid(x, name=None):
     return -ivy.softplus(-x)
 
 
+@to_ivy_arrays_and_back
+def log1p(x, name=None):
+    return ivy.log1p(x)
+
+
 @to_ivy_arrays_and_back
 def logical_and(x, y, name="LogicalAnd"):
     return ivy.logical_and(x, y)
diff --git a/ivy/functional/frontends/tensorflow/raw_ops.py b/ivy/functional/frontends/tensorflow/raw_ops.py
--- a/ivy/functional/frontends/tensorflow/raw_ops.py
+++ b/ivy/functional/frontends/tensorflow/raw_ops.py
@@ -277,9 +277,7 @@ def Log(*, x, name="Log"):
     return ivy.log(x)
 
 
-@to_ivy_arrays_and_back
-def Log1p(*, x, name="Log1p"):
-    return ivy.log1p(x)
+Log1p = to_ivy_arrays_and_back(map_raw_ops_alias(tf_frontend.math.log1p))
 
 
 LogicalOr = to_ivy_arrays_and_back(map_raw_ops_alias(tf_frontend.math.logical_or))


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_math.py b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_math.py
--- a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_math.py
+++ b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_math.py
@@ -470,6 +470,34 @@ def test_tensorflow_log_sigmoid(
     )
 
 
+# log1p
+@handle_frontend_test(
+    fn_tree="tensorflow.math.log1p",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+        safety_factor_scale="log",
+    ),
+    test_with_out=st.just(False),
+)
+def test_tensorflow_log1p(
+    *,
+    dtype_and_x,
+    frontend,
+    test_flags,
+    fn_tree,
+    on_device,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        x=x[0],
+    )
+
+
 # reciprocal
 @handle_frontend_test(
     fn_tree="tensorflow.math.reciprocal",
diff --git a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py
--- a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py
@@ -1413,6 +1413,7 @@ def test_tensorflow_Log(  # NOQA
     fn_tree="tensorflow.raw_ops.Log1p",
     dtype_and_x=helpers.dtype_and_values(
         available_dtypes=helpers.get_dtypes("float"),
+        safety_factor_scale="log",
     ),
     test_with_out=st.just(False),
 )
Repository: ivy-llc/ivy

Issue:
softplus



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/tensorflow/math.py b/ivy/functional/frontends/tensorflow/math.py
--- a/ivy/functional/frontends/tensorflow/math.py
+++ b/ivy/functional/frontends/tensorflow/math.py
@@ -583,6 +583,11 @@ def softmax(logits, axis=-1):
     return ivy.softmax(logits, axis=axis)
 
 
+@to_ivy_arrays_and_back
+def softplus(features, name=None):
+    return ivy.softplus(features)
+
+
 @to_ivy_arrays_and_back
 def xlogy(x, y, name=None):
     return ivy.xlogy(x, y)


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_math.py b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_math.py
--- a/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_math.py
+++ b/ivy_tests/test_ivy/test_frontends/test_tensorflow/test_math.py
@@ -75,7 +75,6 @@ def test_tensorflow_add(
     fn_tree="tensorflow.math.sin",
     dtype_and_x=helpers.dtype_and_values(available_dtypes=helpers.get_dtypes("float")),
     test_with_out=st.just(False),
-
 )
 def test_tensorflow_sin(
     *,
@@ -2051,6 +2050,31 @@ def test_tensorflow_softmax(
     )
 
 
+# softplus
+@handle_frontend_test(
+    fn_tree="tensorflow.math.softplus",
+    dtype_and_x=helpers.dtype_and_values(available_dtypes=helpers.get_dtypes("float")),
+    test_with_out=st.just(False),
+)
+def test_tensorflow_softplus(
+    *,
+    dtype_and_x,
+    frontend,
+    test_flags,
+    fn_tree,
+    on_device,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        frontend=frontend,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        features=x[0],
+    )
+
+
 # xlogy
 @handle_frontend_test(
     fn_tree="tensorflow.math.xlogy",
Repository: ivy-llc/ivy

Issue:
arccosh



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/torch/tensor.py b/ivy/functional/frontends/torch/tensor.py
--- a/ivy/functional/frontends/torch/tensor.py
+++ b/ivy/functional/frontends/torch/tensor.py
@@ -254,6 +254,10 @@ def arctanh_(self):
     def log(self):
         return torch_frontend.log(self._ivy_array)
 
+    @with_unsupported_dtypes({"1.11.0 and below": ("float16",)}, "torch")
+    def arccosh(self):
+        return torch_frontend.arccosh(self._ivy_array)
+
     @with_unsupported_dtypes({"1.11.0 and below": ("float16",)}, "torch")
     def log_(self):
         self._ivy_array = self.log().ivy_array


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
@@ -3813,6 +3813,41 @@ def test_torch_instance_argsort(
     )
 
 
+# arccosh
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="arccosh",
+    dtype_and_x=helpers.dtype_and_values(
+        min_value=-1.0,
+        max_value=1.0,
+        available_dtypes=helpers.get_dtypes("float"),
+    ),
+)
+def test_torch_instance_arccosh(
+    dtype_and_x,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        init_all_as_kwargs_np={
+            "data": x[0],
+        },
+        method_input_dtypes=[],
+        method_all_as_kwargs_np={},
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+    )
+
+
 # ceil
 @handle_frontend_method(
     class_tree=CLASS_TREE,
Repository: ivy-llc/ivy

Issue:
arccosh_



Discussion:

Resolving patch:
diff --git a/ivy/functional/frontends/torch/tensor.py b/ivy/functional/frontends/torch/tensor.py
--- a/ivy/functional/frontends/torch/tensor.py
+++ b/ivy/functional/frontends/torch/tensor.py
@@ -400,6 +400,11 @@ def acos_(self):
         self._ivy_array = self.acos().ivy_array
         return self
 
+    @with_unsupported_dtypes({"1.11.0 and below": ("float16",)}, "torch")
+    def arccosh_(self):
+        self.ivy_array = self.arccosh().ivy_array
+        return self
+
     @with_unsupported_dtypes({"1.11.0 and below": ("float16",)}, "torch")
     def arccos(self):
         return torch_frontend.arccos(self._ivy_array)


Test patch:
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_tensor.py
@@ -3675,6 +3675,41 @@ def test_torch_special_pow(
     )
 
 
+# arccosh_
+@handle_frontend_method(
+    class_tree=CLASS_TREE,
+    init_tree="torch.tensor",
+    method_name="arccosh_",
+    dtype_and_x=helpers.dtype_and_values(
+        min_value=-1.0,
+        max_value=1.0,
+        available_dtypes=helpers.get_dtypes("float"),
+    ),
+)
+def test_torch_instance_arccosh_(
+    dtype_and_x,
+    frontend_method_data,
+    init_flags,
+    method_flags,
+    frontend,
+    on_device,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_method(
+        init_input_dtypes=input_dtype,
+        init_all_as_kwargs_np={
+            "data": x[0],
+        },
+        method_input_dtypes=[],
+        method_all_as_kwargs_np={},
+        frontend_method_data=frontend_method_data,
+        init_flags=init_flags,
+        method_flags=method_flags,
+        frontend=frontend,
+        on_device=on_device,
+    )
+
+
 # argmax
 @handle_frontend_method(
     class_tree=CLASS_TREE,