#16310: update digamma docs

tenstorrent · Jan 23, 2025 · ac7755a · ac7755a
1 parent 78f2c0b
commit ac7755a
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Showing 3 changed files with 6 additions and 4 deletions.
diff --git a/tests/sweep_framework/sweeps/eltwise/unary/digamma/digamma.py b/tests/sweep_framework/sweeps/eltwise/unary/digamma/digamma.py
@@ -47,7 +47,7 @@ def run(
     torch.manual_seed(0)
 
     torch_input_tensor = gen_func_with_cast_tt(
-        partial(torch_random, low=0.0001, high=100, dtype=torch.float32), input_dtype
+        partial(torch_random, low=1, high=100, dtype=torch.float32), input_dtype
     )(input_shape)
     golden_function = ttnn.get_golden_function(ttnn.digamma)
     torch_output_tensor = golden_function(torch_input_tensor)
@@ -58,6 +58,7 @@ def run(
         layout=input_layout,
         device=device,
         memory_config=input_memory_config,
+        pad_value=1,
     )
 
     start_time = start_measuring_time()

diff --git a/tests/sweep_framework/sweeps/eltwise/unary/digamma/digamma_sharded.py b/tests/sweep_framework/sweeps/eltwise/unary/digamma/digamma_sharded.py
@@ -92,7 +92,7 @@ def run(
     )
 
     torch_input_tensor_a = gen_func_with_cast_tt(
-        partial(torch_random, low=0.0001, high=100, dtype=torch.float32), input_a_dtype
+        partial(torch_random, low=1, high=100, dtype=torch.float32), input_a_dtype
     )(input_shape)
     golden_function = ttnn.get_golden_function(ttnn.digamma)
     torch_output_tensor = golden_function(torch_input_tensor_a)
@@ -103,6 +103,7 @@ def run(
         layout=input_layout,
         device=device,
         memory_config=sharded_config,
+        pad_value=1,
     )
 
     start_time = start_measuring_time()

diff --git a/ttnn/cpp/ttnn/operations/eltwise/unary/unary_pybind.hpp b/ttnn/cpp/ttnn/operations/eltwise/unary/unary_pybind.hpp
@@ -1666,8 +1666,8 @@ void py_module(py::module& module) {
         R"doc(System memory is not supported.)doc");
     detail::bind_unary_composite(module, ttnn::cbrt, R"doc(Performs cbrt function on :attr:`input_tensor`.)doc");
     detail::bind_unary_composite(module, ttnn::cosh, R"doc(Performs cosh function on :attr:`input_tensor`.)doc", "[supported range -9 to 9]", R"doc(BFLOAT16, BFLOAT8_B)doc");
-    detail::bind_unary_composite(module, ttnn::digamma, R"doc(Performs digamma function on :attr:`input_tensor`.)doc", "[supported for values greater than 0].",
-        R"doc(BFLOAT16, BFLOAT8_B)doc", R"doc(TILE)doc", R"doc(2, 3, 4)doc", "", R"doc(torch.tensor([[2, 3], [4, 5]], dtype=torch.bfloat16))doc");
+    detail::bind_unary_composite(module, ttnn::digamma, R"doc(Performs digamma function on :attr:`input_tensor`.)doc", "[supported range 1 to inf].",
+        R"doc(BFLOAT16, BFLOAT8_B)doc", R"doc(TILE)doc", R"doc(2, 3, 4)doc", "For BFLOAT8_B, the padding value must be set to 1 due to BFLOAT8_B limitations.More information about the `BFLOAT8_B  <../tensor.html#limitation-of-bfloat8-b>`_.", R"doc(torch.tensor([[2, 3], [4, 5]], dtype=torch.bfloat16))doc");
     detail::bind_unary_composite(module, ttnn::lgamma, R"doc(Performs lgamma function on :attr:`input_tensor`.)doc", "[supported for value greater than 0].", R"doc(BFLOAT16)doc");
     detail::bind_unary_composite(module, ttnn::log1p, R"doc(Performs log1p function on :attr:`input_tensor`.)doc", "[supported range -1 to 1].", R"doc(BFLOAT16, BFLOAT8_B)doc");
     detail::bind_unary_composite(module, ttnn::mish, R"doc(Performs mish function on :attr:`input_tensor`.)doc", "[supported range -20 to inf].", R"doc(BFLOAT16, BFLOAT8_B)doc",