diff --git a/ivy/functional/frontends/torch/miscellaneous_ops.py b/ivy/functional/frontends/torch/miscellaneous_ops.py
index 0f1d694e32e50..c5892f3b51afa 100644
--- a/ivy/functional/frontends/torch/miscellaneous_ops.py
+++ b/ivy/functional/frontends/torch/miscellaneous_ops.py
@@ -236,6 +236,22 @@ def gcd(input, other, *, out=None):
     return ivy.gcd(input, other, out=out)
 
 
+@to_ivy_arrays_and_back
+def histc(input, bins=100, min=0, max=0, *, out=None):
+    input_ivy = ivy.flatten(
+        input
+    )  # torch.histc results in a 1D tensor so I flattened it out.
+    if min == 0 and max == 0:
+        min = ivy.min(input_ivy)
+        max = ivy.max(input_ivy)
+    if min == max:
+        range = (min - 1e-2, min + 1e-2)
+    else:
+        range = (min, max)
+
+    return ivy.histogram(input_ivy, bins=bins, range=range, axis=0)
+
+
 @to_ivy_arrays_and_back
 def kron(input, other, *, out=None):
     return ivy.kron(input, other, out=out)
@@ -541,3 +557,22 @@ def view_as_real(input):
     re_part = ivy.real(input)
     im_part = ivy.imag(input)
     return ivy.stack((re_part, im_part), axis=-1)
+
+
+@to_ivy_arrays_and_back
+@with_supported_dtypes({"2.0.1 and below": ("float32", "float64")},
+def histc(input, bins=100, min=0, max=0, *, out= None):
+
+    input_ivy = ivy.flatten(input) # torch.histc results in a 1D tensor so I flattened it out.
+
+    if min ==0 and max ==0:
+        min = ivy.min(input_ivy); max = ivy.max(input_ivy)
+    if min == max:
+        min = min - 5.000000e-01
+        max = max + 5.000000e-01
+
+    range = (min , max)
+    if range[0] > range[1]:
+      raise ivy.exceptions.IvyError("Max must be greater than or equal to min")
+
+    return ivy.histogram(input_ivy, bins = bins, range=range, axis =0, out =out, dtype = input.dtype)
diff --git a/ivy_tests/test_ivy/test_frontends/test_torch/test_miscellaneous_ops.py b/ivy_tests/test_ivy/test_frontends/test_torch/test_miscellaneous_ops.py
index 992c6a7689d1e..cbebf32cb7f45 100644
--- a/ivy_tests/test_ivy/test_frontends/test_torch/test_miscellaneous_ops.py
+++ b/ivy_tests/test_ivy/test_frontends/test_torch/test_miscellaneous_ops.py
@@ -1143,6 +1143,34 @@ def test_torch_gcd(
     )
 
 
+# histc
+@handle_frontend_test(
+    fn_tree="torch.histc",
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("float"),
+    ),
+)
+def test_torch_histc(
+    *,
+    dtype_and_x,
+    on_device,
+    fn_tree,
+    frontend,
+    backend_fw,
+    test_flags,
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        frontend=frontend,
+        backend_to_test=backend_fw,
+        test_flags=test_flags,
+        fn_tree=fn_tree,
+        on_device=on_device,
+        input=x[0],
+    )
+
+
 # kron
 @handle_frontend_test(
     fn_tree="torch.kron",
@@ -1813,14 +1841,48 @@ def test_torch_view_as_real(
     on_device,
     fn_tree,
     frontend,
+    backend_fw,
     test_flags,
 ):
     input_dtype, x = dtype_and_x
     helpers.test_frontend_function(
         input_dtypes=input_dtype,
         frontend=frontend,
+        backend_to_test=backend_fw,
         test_flags=test_flags,
         fn_tree=fn_tree,
         on_device=on_device,
         input=np.asarray(x[0], dtype=input_dtype[0]),
     )
+<<<<<<< HEAD
+=======
+
+
+# histc
+@handle_frontend_test(
+        fn_tree= "torch.histc",
+        dtype_and_x = helpers.dtype_and_values(
+            available_dtypes= helpers.get_dtypes("float"),
+        ),
+    )
+
+def test_torch_histc(
+    *,
+    dtype_and_x,
+    on_device,
+    fn_tree,
+    frontend,
+    backend_fw,
+    test_flags,
+):
+    input_dtype , x = dtype_and_x
+    helpers.test_frontend_function(
+        input_dtypes= input_dtype,
+        frontend=frontend,
+        backend_to_test=backend_fw,
+        test_flags = test_flags,
+        fn_tree= fn_tree,
+        on_device=on_device,
+        input=np.asarray(x[0], dtype=input_dtype[0]),
+    )
+>>>>>>> 0e45c14f2 (Changed histc for min==max case)