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#7996: Update documentation and sweep config
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@mcw-anasuya
mcw-anasuya committed Oct 18, 2024
1 parent b0d451b commit f5a9380
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Showing 3 changed files with 47 additions and 22 deletions.
26 changes: 14 additions & 12 deletions tests/sweep_framework/sweeps/eltwise/binary/multiply/multiply.py
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Original file line number Diff line number Diff line change
Expand Up @@ -6,20 +6,13 @@
from functools import partial

import torch
import random
import ttnn
from tests.sweep_framework.utils import gen_shapes
from tests.tt_eager.python_api_testing.sweep_tests.generation_funcs import gen_func_with_cast_tt

from tests.ttnn.utils_for_testing import check_with_pcc, start_measuring_time, stop_measuring_time
from models.utility_functions import torch_random

# Override the default timeout in seconds for hang detection.
TIMEOUT = 30

random.seed(0)


# Parameters provided to the test vector generator are defined here.
# They are defined as dict-type suites that contain the arguments to the run function as keys, and lists of possible inputs as values.
# Each suite has a key name (in this case "suite_1" and "suite_2") which will associate the test vectors to this specific suite of inputs.
Expand All @@ -29,15 +22,24 @@
"input_shape": gen_shapes([1, 1, 32, 32], [6, 12, 256, 256], [1, 1, 32, 32], 32),
"input_a_dtype": [ttnn.bfloat16, ttnn.bfloat8_b],
"input_b_dtype": [ttnn.bfloat16, ttnn.bfloat8_b],
"input_a_layout": [ttnn.TILE_LAYOUT],
"input_b_layout": [ttnn.TILE_LAYOUT],
"input_a_layout": [ttnn.TILE_LAYOUT, ttnn.ROW_MAJOR_LAYOUT],
"input_b_layout": [ttnn.TILE_LAYOUT, ttnn.ROW_MAJOR_LAYOUT],
"input_a_memory_config": [ttnn.DRAM_MEMORY_CONFIG, ttnn.L1_MEMORY_CONFIG],
"input_b_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 or test_vector["input_b_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.
Expand All @@ -54,8 +56,7 @@ def run(
*,
device,
) -> list:
data_seed = random.randint(0, 20000000)
torch.manual_seed(data_seed)
torch.manual_seed(0)

torch_input_tensor_a = gen_func_with_cast_tt(
partial(torch_random, low=-100, high=100, dtype=torch.float32), input_a_dtype
Expand All @@ -64,7 +65,8 @@ def run(
partial(torch_random, low=-100, high=100, dtype=torch.float32), input_b_dtype
)(input_shape)

torch_output_tensor = torch.mul(torch_input_tensor_a, torch_input_tensor_b)
golden_function = ttnn.get_golden_function(ttnn.multiply)
torch_output_tensor = golden_function(torch_input_tensor_a, torch_input_tensor_b)

input_tensor_a = ttnn.from_torch(
torch_input_tensor_a,
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23 changes: 15 additions & 8 deletions tests/sweep_framework/sweeps/eltwise/binary/subtract/subtract.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,9 +14,6 @@
from tests.ttnn.utils_for_testing import check_with_pcc, start_measuring_time, stop_measuring_time
from models.utility_functions import torch_random

# Override the default timeout in seconds for hang detection.
TIMEOUT = 30

random.seed(0)

# Parameters provided to the test vector generator are defined here.
Expand All @@ -26,17 +23,26 @@
parameters = {
"nightly": {
"input_shape": gen_shapes([1, 1, 32, 32], [6, 12, 256, 256], [1, 1, 32, 32], 32),
"input_a_dtype": [ttnn.bfloat16],
"input_b_dtype": [ttnn.bfloat16],
"input_a_layout": [ttnn.TILE_LAYOUT],
"input_b_layout": [ttnn.TILE_LAYOUT],
"input_a_dtype": [ttnn.bfloat16, ttnn.bfloat8_b],
"input_b_dtype": [ttnn.bfloat16, ttnn.bfloat8_b],
"input_a_layout": [ttnn.ROW_MAJOR_LAYOUT, ttnn.TILE_LAYOUT],
"input_b_layout": [ttnn.ROW_MAJOR_LAYOUT, ttnn.TILE_LAYOUT],
"input_a_memory_config": [ttnn.DRAM_MEMORY_CONFIG, ttnn.L1_MEMORY_CONFIG],
"input_b_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 or test_vector["input_b_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.
Expand All @@ -60,7 +66,8 @@ def run(
partial(torch_random, low=-100, high=100, dtype=torch.float32), input_b_dtype
)(input_shape)

torch_output_tensor = torch.sub(torch_input_tensor_a, torch_input_tensor_b)
golden_function = ttnn.get_golden_function(ttnn.subtract)
torch_output_tensor = golden_function(torch_input_tensor_a, torch_input_tensor_b)

input_tensor_a = ttnn.from_torch(
torch_input_tensor_a,
Expand Down
20 changes: 18 additions & 2 deletions ttnn/cpp/ttnn/operations/eltwise/binary/binary_pybind.hpp
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Original file line number Diff line number Diff line change
Expand Up @@ -743,7 +743,15 @@ void py_module(py::module& module) {
ttnn::subtract,
R"doc(Subtracts :attr:`input_tensor_b` from :attr:`input_tensor_a` and returns the tensor with the same layout as :attr:`input_tensor_a`)doc",
R"doc(\mathrm{{output\_tensor}}_i = (\mathrm{{input\_tensor\_a}}_i - \mathrm{{input\_tensor\_b}}_i))doc",
R"doc(: :code:`'None'` | :code:`'relu'`. )doc");
R"doc(: :code:`'None'` | :code:`'relu'`. )doc",
R"doc(Supported dtypes, layouts, and ranks:
+----------------------------+---------------------------------+-------------------+
| Dtypes | Layouts | Ranks |
+----------------------------+---------------------------------+-------------------+
| BFLOAT16, BFLOAT8_B | TILE | 2, 3, 4 |
+----------------------------+---------------------------------+-------------------+
)doc");

detail::bind_binary_inplace_operation(
module,
Expand All @@ -756,7 +764,15 @@ void py_module(py::module& module) {
ttnn::multiply,
R"doc(Multiplies :attr:`input_tensor_a` by :attr:`input_tensor_b` and returns the tensor with the same layout as :attr:`input_tensor_a`)doc",
R"doc(\mathrm{{output\_tensor}}_i = (\mathrm{{input\_tensor\_a}}_i * \mathrm{{input\_tensor\_b}}_i))doc",
R"doc(: :code:`'None'` | :code:`'relu'`. )doc");
R"doc(: :code:`'None'` | :code:`'relu'`. )doc",
R"doc(Supported dtypes, layouts, and ranks:
+----------------------------+---------------------------------+-------------------+
| Dtypes | Layouts | Ranks |
+----------------------------+---------------------------------+-------------------+
| BFLOAT16, BFLOAT8_B | TILE | 2, 3, 4 |
+----------------------------+---------------------------------+-------------------+
)doc");

detail::bind_binary_inplace_operation(
module,
Expand Down

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