def render_tensor_sandbox(hide_function_defs: bool):
st.write("## Sandbox for Tensors")
st.write("**Define your tensor**")
# Consistent random number generator
rng = np.random.RandomState(42)
# col1, col2 = st.beta_columns(2)
tensor_shape = st_eval_error_message(
st.text_input("Tensor shape", value="(2, 2, 2)"),
"Tensor shape must be defined as an in-line tuple, i.e. (2, 2, 2)",
)
tensor_size = int(operators.prod(tensor_shape))
random_tensor = st.checkbox("Fill tensor with random numbers", value=True)
if random_tensor:
tensor_data = np.round(rng.rand(tensor_size), 2)
st.write("**Tensor data storage:**")
# Visualize horizontally
st.write(tensor_data.reshape(1, -1))
else:
tensor_data = st_eval_error_message(
st.text_input("Tensor data storage",
value=str(list(range(tensor_size)))),
"Tensor data storage must be defined as an in-line list, i.e. [1, 2, 3, 4]",
)
try:
test_tensor = Tensor.make(tensor_data,
tensor_shape,
backend=TensorFunctions)
except AssertionError as e:
storage_size = len(tensor_data)
if tensor_size != storage_size:
st.error(
f"Tensor data storage must define all values in shape ({tensor_size} != {storage_size })"
)
else:
st.error(e)
return
select_fn = {
"Visualize Tensor Definition": interface_visualize_tensor,
"Visualize Tensor Strides": interface_strides,
"function: index_to_position": interface_index_to_position,
"function: to_index": interface_to_index,
"function: TensorData.permute": interface_permute,
}
selected_fn = st.selectbox("Select an interface",
options=list(select_fn.keys()))
select_fn[selected_fn](test_tensor, hide_function_defs)
def test_prod(x, y, z):
assert_close(operators.prod([x, y, z]), x * y * z)
def test_prod(x, y, z):
assert_close(prod([x, y, z]), x * y * z)
