#8158: Update heaviside sweep config and doc (#13240)

* #8158: Update heaviside sweep config and doc

* #8158: Move sweep test

tests/sweep_framework/sweeps/eltwise/unary/heaviside/heaviside.py

@@ -29,14 +29,23 @@
         "input_shape": gen_shapes([1, 1, 32, 32], [6, 12, 256, 256], [1, 1, 32, 32], 16)
         + gen_shapes([1, 32, 32], [12, 256, 256], [1, 32, 32], 16)
         + gen_shapes([32, 32], [256, 256], [32, 32], 16),
-        "input_a_dtype": [ttnn.bfloat16],
-        "input_a_layout": [ttnn.TILE_LAYOUT],
+        "input_a_dtype": [ttnn.bfloat16, ttnn.bfloat8_b],
+        "input_a_layout": [ttnn.TILE_LAYOUT, ttnn.ROW_MAJOR_LAYOUT],
         "input_a_memory_config": [ttnn.DRAM_MEMORY_CONFIG, ttnn.L1_MEMORY_CONFIG],
         "output_memory_config": [ttnn.DRAM_MEMORY_CONFIG, ttnn.L1_MEMORY_CONFIG],
     },
 }
 
 
+# Invalidate vector is called during the generation phase where each vector will be passed in.
+# If invalidated, the vector will still be stored but will be skipped.
+# Returns False, None if the vector is valid, and True, str with a reason for invalidation if it is invalid.
+def invalidate_vector(test_vector) -> Tuple[bool, Optional[str]]:
+    if test_vector["input_a_layout"] == ttnn.ROW_MAJOR_LAYOUT:
+        return True, "Row Major layout is not supported"
+    return False, None
+
+
 # This is the run instructions for the test, defined by the developer.
 # The run function must take the above-defined parameters as inputs.
 # The runner will call this run function with each test vector, and the returned results from this function will be stored.
@@ -58,7 +67,9 @@ def run(
     )(input_shape)
 
     scalar = torch.tensor(1, dtype=torch.bfloat16).uniform_(-100, 100)
-    torch_output_tensor = torch.heaviside(torch_input_tensor_a, scalar)
+
+    golden_function = ttnn.get_golden_function(ttnn.heaviside)
+    torch_output_tensor = golden_function(torch_input_tensor_a, value=scalar)
 
     input_tensor_a = ttnn.from_torch(
         torch_input_tensor_a,

ttnn/cpp/ttnn/operations/eltwise/unary/unary_pybind.hpp

@@ -1565,7 +1565,16 @@ void py_module(py::module& module) {
 
         )doc");
 
-    detail::bind_unary_operation_with_float_parameter(module, ttnn::heaviside, "value", "The value parameter for the Heaviside function", "");
+    detail::bind_unary_operation_with_float_parameter(module, ttnn::heaviside, "value", "The value parameter for the Heaviside function", "",
+        R"doc(Supported dtypes, layouts, and ranks:
+           +----------------------------+---------------------------------+-------------------+
+           |     Dtypes                 |         Layouts                 |     Ranks         |
+           +----------------------------+---------------------------------+-------------------+
+           |    BFLOAT16, BFLOAT8_B     |          TILE                   |      2, 3, 4      |
+           +----------------------------+---------------------------------+-------------------+
+
+        )doc");
+
     detail::bind_unary_operation_with_float_parameter(module, ttnn::leaky_relu, "negative_slope", "The slope parameter for the Leaky ReLU function", "");
     detail::bind_unary_operation_with_float_parameter(module, ttnn::relu_max, "upper_limit", "The max value for ReLU function", "This function caps off the input to a max value and a min value of 0");
     detail::bind_unary_operation_with_float_parameter(module, ttnn::relu_min, "lower_limit", "The min value for ReLU function", "This will carry out ReLU operation at min value instead of the standard 0");