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5f923cd | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 | // Copyright 2025 The ODML Authors.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "runtime/components/scoring_cpu_util.h"
#include <algorithm>
#include <cmath>
#include <iterator>
#include <vector>
#include "absl/status/status.h" // from @com_google_absl
#include "absl/status/statusor.h" // from @com_google_absl
#include "absl/strings/str_cat.h" // from @com_google_absl
#include "absl/types/span.h" // from @com_google_absl
#include "runtime/components/sampling_cpu_util.h"
#include "runtime/util/status_macros.h" // IWYU pragma: keep
namespace litert::lm {
absl::StatusOr<std::vector<float>> ComputeLogLikelihood(
absl::Span<const float> logits, absl::Span<const int> sampled_ids,
float temperature) {
const int batch_size = sampled_ids.size();
const int vocab_size = logits.size() / batch_size;
for (int i = 0; i < batch_size; ++i) {
if (sampled_ids[i] < 0 || sampled_ids[i] >= vocab_size) {
return absl::InvalidArgumentError(
absl::StrCat("Invalid sampled id: ", sampled_ids[i]));
}
}
// Get all indices and their probabilities for calculating perplexity.
ASSIGN_OR_RETURN(
auto all_token_ids,
TopKTokenIds(logits, vocab_size, batch_size, /*sequence_size=*/1));
std::vector<int> flat_all_token_ids(batch_size * vocab_size);
for (int b = 0; b < batch_size; ++b) {
std::copy(all_token_ids[b].begin(), all_token_ids[b].end(),
flat_all_token_ids.begin() + b * vocab_size);
}
std::vector<std::vector<float>> all_logit_values;
ASSIGN_OR_RETURN(auto all_probabilities,
Softmax(logits, flat_all_token_ids, temperature, batch_size,
/*sequence_size=*/1, all_logit_values));
std::vector<float> batch_confidence(batch_size);
for (int b = 0; b < batch_size; ++b) {
if (sampled_ids[b] >= 0 && sampled_ids[b] < vocab_size) {
// Find the index of the sampled token id in the flat_all_token_ids array
auto it = std::find(all_token_ids[b].begin(), all_token_ids[b].end(),
sampled_ids[b]);
if (it != all_token_ids[b].end()) {
int index_in_topk = std::distance(all_token_ids[b].begin(), it);
batch_confidence[b] = std::log(all_probabilities[b][index_in_topk]);
} else {
return absl::InternalError("Sampled ID not found in top-k tokens");
}
}
}
return batch_confidence;
}
} // namespace litert::lm
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