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error and errorsquaredNorm optional data #105

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merged 10 commits into from
Mar 14, 2022
Merged

error and errorsquaredNorm optional data #105

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c200aa4
error and errorsquaredNorm optional data
jeffin07 Mar 8, 2022
a2a6c72
changes after reivew
jeffin07 Mar 10, 2022
8d07d9c
changes in unit test after review
jeffin07 Mar 10, 2022
034a8e1
variable checking in unit test after review
jeffin07 Mar 10, 2022
fc69592
test for varibale change in objective
jeffin07 Mar 11, 2022
7237825
variable checking function in unit test
jeffin07 Mar 11, 2022
f5cecb7
Merge remote-tracking branch 'upstream/main' into objective-error
jeffin07 Mar 11, 2022
07058e3
Merge remote-tracking branch 'upstream/main' into objective-error
jeffin07 Mar 12, 2022
ddeeedd
commom test function for objective error
jeffin07 Mar 12, 2022
1da20bc
unit test changes after review
jeffin07 Mar 14, 2022
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unit test changes after review
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@jeffin07
jeffin07 committed Mar 14, 2022
commit 1da20bc6743649d7b7ee6f867c311e4a9a17f576
45 changes: 29 additions & 16 deletions theseus/core/tests/test_objective.py
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Original file line number Diff line number Diff line change
Expand Up @@ -256,11 +256,6 @@ def _check_error_for_data(v1_data_, v2_data_, error_, error_type):
else:
assert error_.allclose(expected_error.norm(dim=1) ** 2)

# def _check_error_for_data(v1_data_, v2_data_, error_, error_norm_2_):
# expected_error = torch.cat([v1_data_, v2_data_], dim=1) * w
# assert error_.allclose(expected_error)
# assert error_norm_2_.allclose(expected_error.norm(dim=1) ** 2)

def _check_variables(objective, input_data, v1_data, v2_data, also_update):

if also_update:
Expand All @@ -273,7 +268,7 @@ def _check_variables(objective, input_data, v1_data, v2_data, also_update):
assert objective.optim_vars["v1"].data is v1_data
assert objective.optim_vars["v2"].data is v2_data

def _check_error(
def _check_error_and_variables(
v1_data_, v2_data_, error_, error_type, objective, input_data, also_update
):

Expand Down Expand Up @@ -313,9 +308,10 @@ def _check_error(
v2_data_new = torch.ones(batch_size, dof) * f2 * 0.1

input_data = {"v1": v1_data_new, "v2": v2_data_new}

error = objective.error(input_data=input_data, also_update=False)

_check_error(
_check_error_and_variables(
v1_data_new,
v2_data_new,
error,
Expand All @@ -325,11 +321,16 @@ def _check_error(
also_update=False,
)

v1_data_new = torch.ones(batch_size, dof) * f1 * 0.3
v2_data_new = torch.ones(batch_size, dof) * f2 * 0.3

input_data = {"v1": v1_data_new, "v2": v2_data_new}

error_norm_2 = objective.error_squared_norm(
input_data=input_data, also_update=False
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)

_check_error(
_check_error_and_variables(
v1_data_new,
v2_data_new,
error_norm_2,
Expand All @@ -339,23 +340,35 @@ def _check_error(
also_update=False,
)

v1_data = torch.ones(batch_size, dof) * f1 * 0.4
v2_data = torch.ones(batch_size, dof) * f2 * 0.4
v1_data_new = torch.ones(batch_size, dof) * f1 * 0.4
v2_data_new = torch.ones(batch_size, dof) * f2 * 0.4

input_data = {"v1": v1_data_new, "v2": v2_data_new}

input_data = {"v1": v1_data, "v2": v2_data}
error = objective.error(input_data=input_data, also_update=True)

_check_error(
v1_data, v2_data, error, "error", objective, input_data, also_update=True
_check_error_and_variables(
v1_data_new,
v2_data_new,
error,
"error",
objective,
input_data,
also_update=True,
)

v1_data_new = torch.ones(batch_size, dof) * f1 * 0.4
v2_data_new = torch.ones(batch_size, dof) * f2 * 0.4

input_data = {"v1": v1_data_new, "v2": v2_data_new}

error_norm_2 = objective.error_squared_norm(
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input_data=input_data, also_update=True
)

_check_error(
v1_data,
v2_data,
_check_error_and_variables(
v1_data_new,
v2_data_new,
error_norm_2,
"error_norm_2",
objective,
Expand Down