frontend tensorflow.raw_ops Update (#4860)

ivy/functional/frontends/tensorflow/raw_ops.py

@@ -2,6 +2,11 @@
 import ivy
 
 
+def AddN(*, inputs, name="AddN"):
+    inputs = ivy.array(inputs)
+    return ivy.sum(inputs, axis=0, dtype=inputs.dtype)
+
+
 def Acos(*, x, name="Acos"):
     return ivy.acos(x)
 
@@ -63,6 +68,16 @@ def Cosh(*, x, name="cosh"):
     return ivy.cosh(x)
 
 
+def Equal(*, x, y, incompatible_shape_error=True, name="Equal"):
+    if incompatible_shape_error:
+        return ivy.equal(x, y)
+
+    try:
+        ivy.equal(x, y)
+    except (ivy.exceptions.IvyError, ivy.exceptions.IvyBackendException):
+        return ivy.array(False)
+
+
 def Exp(*, x, name="Exp"):
     return ivy.exp(x)
 
@@ -95,11 +110,11 @@ def Log(*, x, name="Log"):
     return ivy.log(x)
 
 
-def LogicalOr(*, x, y, name=None):
+def LogicalOr(*, x, y, name="LogicalOr"):
     return ivy.logical_or(x, y)
 
 
-def LogicalNot(*, x, name=None):
+def LogicalNot(*, x, name="LogicalNot"):
     return ivy.logical_not(x)
 
 
@@ -111,6 +126,20 @@ def Minimum(*, x, y, name="Minimum"):
     return ivy.minimum(x, y)
 
 
+def Neg(*, x, name="Neg"):
+    return ivy.negative(x)
+
+
+def NotEqual(*, x, y, incompatible_shape_error=True, name="NotEqual"):
+    if incompatible_shape_error:
+        return ivy.not_equal(x, y)
+
+    try:
+        ivy.not_equal(x, y)
+    except (ivy.exceptions.IvyError, ivy.exceptions.IvyBackendException):
+        return ivy.array(False)
+
+
 def Reshape(*, tensor, shape, name="Reshape"):
     return ivy.reshape(tensor, shape)
 

ivy_tests/test_ivy/test_frontends/test_tensorflow/test_raw_ops.py

@@ -1147,3 +1147,126 @@ def test_tensorflow_Shape(
         fn_tree="raw_ops.Shape",
         input=np.asarray(x, dtype=input_dtype),
     )
+
+
+# AddN
+@handle_cmd_line_args
+@given(
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("numeric"),
+        min_num_dims=1,
+    ),
+    num_positional_args=helpers.num_positional_args(
+        fn_name="ivy.functional.frontends.tensorflow.AddN"
+    ),
+)
+def test_tensorflow_AddN(
+    dtype_and_x, as_variable, num_positional_args, native_array, fw
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        as_variable_flags=as_variable,
+        with_out=False,
+        num_positional_args=num_positional_args,
+        native_array_flags=native_array,
+        fw=fw,
+        frontend="tensorflow",
+        fn_tree="raw_ops.AddN",
+        inputs=x,
+    )
+
+
+# Neg
+@handle_cmd_line_args
+@given(
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=[
+            "bfloat16",
+            "float32",
+            "float64",
+            "int8",
+            "int16",
+            "int32",
+            "int64",
+        ],
+    ),
+    num_positional_args=helpers.num_positional_args(
+        fn_name="ivy.functional.frontends.tensorflow.Neg"
+    ),
+)
+def test_tensorflow_Neg(
+    dtype_and_x, as_variable, num_positional_args, native_array, fw
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        as_variable_flags=as_variable,
+        with_out=False,
+        num_positional_args=num_positional_args,
+        native_array_flags=native_array,
+        fw=fw,
+        frontend="tensorflow",
+        fn_tree="raw_ops.Neg",
+        x=x,
+    )
+
+
+# Equal
+@handle_cmd_line_args
+@given(
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("numeric"),
+        num_arrays=2,
+        shared_dtype=True,
+    ),
+    num_positional_args=helpers.num_positional_args(
+        fn_name="ivy.functional.frontends.tensorflow.Equal"
+    ),
+)
+def test_tensorflow_Equal(
+    dtype_and_x, as_variable, num_positional_args, native_array, fw
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        as_variable_flags=as_variable,
+        with_out=False,
+        num_positional_args=num_positional_args,
+        native_array_flags=native_array,
+        fw=fw,
+        frontend="tensorflow",
+        fn_tree="raw_ops.Equal",
+        x=np.array(x[0], dtype=input_dtype[0]),
+        y=np.array(x[1], dtype=input_dtype[1]),
+    )
+
+
+# NotEqual
+@handle_cmd_line_args
+@given(
+    dtype_and_x=helpers.dtype_and_values(
+        available_dtypes=helpers.get_dtypes("numeric"),
+        num_arrays=2,
+        shared_dtype=True,
+    ),
+    num_positional_args=helpers.num_positional_args(
+        fn_name="ivy.functional.frontends.tensorflow.NotEqual"
+    ),
+)
+def test_tensorflow_NotEqual(
+    dtype_and_x, as_variable, num_positional_args, native_array, fw
+):
+    input_dtype, x = dtype_and_x
+    helpers.test_frontend_function(
+        input_dtypes=input_dtype,
+        as_variable_flags=as_variable,
+        with_out=False,
+        num_positional_args=num_positional_args,
+        native_array_flags=native_array,
+        fw=fw,
+        frontend="tensorflow",
+        fn_tree="raw_ops.NotEqual",
+        x=np.array(x[0], dtype=input_dtype[0]),
+        y=np.array(x[1], dtype=input_dtype[1]),
+    )