Fix imports (#79)

* Fix imports * Fix lint error * Fix lint error(import rule) * Fix lint error(Flake8) * Fix lint error(cpplint)
kakao · Dec 18, 2023 · d068b23 · d068b23
1 parent d2d9b19
commit d068b23
Show file tree

Hide file tree

Showing 4 changed files with 21 additions and 20 deletions.
diff --git a/buffalo/__init__.py b/buffalo/__init__.py
@@ -3,12 +3,13 @@
 __version__ = importlib.metadata.version('buffalo')
 
 from buffalo.algo.als import ALS, inited_CUALS
-from buffalo.algo.eals import EALS
 from buffalo.algo.base import Algo
 from buffalo.algo.bpr import BPRMF, inited_CUBPR
 from buffalo.algo.cfr import CFR
-from buffalo.algo.options import (AlgoOption, ALSOption, EALSOption, BPRMFOption,
-                                  CFROption, PLSIOption, W2VOption, WARPOption)
+from buffalo.algo.eals import EALS
+from buffalo.algo.options import (AlgoOption, ALSOption, BPRMFOption,
+                                  CFROption, EALSOption, PLSIOption, W2VOption,
+                                  WARPOption)
 from buffalo.algo.plsi import PLSI
 from buffalo.algo.w2v import W2V
 from buffalo.algo.warp import WARP

diff --git a/buffalo/algo/eals.py b/buffalo/algo/eals.py
@@ -75,7 +75,7 @@ def init_factors(self):
         for name, rows in [("P", header["num_users"]), ("Q", header["num_items"])]:
             setattr(self, name, None)
             setattr(self, name, np.random.normal(scale=1.0 / (self.opt.d ** 2),
-                                size=(rows, self.vdim)).astype("float32"))
+                    size=(rows, self.vdim)).astype("float32"))
         self.P[:, self.opt.d:] = 0.0
         self.Q[:, self.opt.d:] = 0.0
         self.C = self._get_negative_weights()
@@ -151,17 +151,17 @@ def train(self, training_callback: Optional[Callable[[int, Dict[str, float]], No
             train_t = time.time() - start_t
             metrics = {"train_loss": loss}
             if self.opt.validation and \
-                self.opt.evaluation_on_learning and \
-                self.periodical(self.opt.evaluation_period, i):
-                    start_t = time.time()
-                    self.validation_result = self.get_validation_results()
-                    vali_t = time.time() - start_t
-                    val_str = " ".join([f"{k}:{v:0.5f}" for k, v in self.validation_result.items()])
-                    self.logger.info(f"Validation: {val_str} Elapsed {vali_t:0.3f} secs")
-                    metrics.update({"val_%s" % k: v
-                                    for k, v in self.validation_result.items()})
-                    if training_callback is not None and callable(training_callback):
-                        training_callback(i, metrics)
+               self.opt.evaluation_on_learning and \
+               self.periodical(self.opt.evaluation_period, i):
+                start_t = time.time()
+                self.validation_result = self.get_validation_results()
+                vali_t = time.time() - start_t
+                val_str = " ".join([f"{k}:{v:0.5f}" for k, v in self.validation_result.items()])
+                self.logger.info(f"Validation: {val_str} Elapsed {vali_t:0.3f} secs")
+                metrics.update({"val_%s" % k: v
+                                for k, v in self.validation_result.items()})
+                if training_callback is not None and callable(training_callback):
+                    training_callback(i, metrics)
             self.logger.info("Iteration %d: RMSE %.3f TotalLoss %.3f Elapsed %.3f secs" % (i + 1, loss, (total_loss / self._nnz), train_t))
             best_loss = self.save_best_only(loss, best_loss, i)
             if self.early_stopping(loss):

diff --git a/include/buffalo/misc/blas.hpp b/include/buffalo/misc/blas.hpp
@@ -1,5 +1,8 @@
 #pragma once
 
+#include <string>
+#include <algorithm>
+
 
 extern "C" {
 // blas subroutines

diff --git a/tests/algo/test_eals.py b/tests/algo/test_eals.py
@@ -1,9 +1,6 @@
 import unittest
 
-from loguru import logger
-
-import buffalo
-from buffalo import EALS, EALSOption, aux, set_log_level, MatrixMarketOptions, set_log_level
+from buffalo import EALS, EALSOption, aux, set_log_level
 
 from .base import TestBase
 
@@ -61,7 +58,7 @@ def test07_train_ml_20m(self):
         opt.num_workers = 8
         opt.validation = aux.Option({"topk": 10})
         self._test7_train_ml_20m(EALS, opt)
-    
+
     def test08_serialization(self):
         opt = EALSOption().get_default_option()
         opt.d = 5