Add file path to io error messages (#1523)

test/torchaudio_unittest/backend/sox_io/info_test.py

@@ -476,3 +476,14 @@ class TestFileObjectHttp(HttpServerMixin, FileObjTestBase, PytorchTestCase):
         assert sinfo.num_frames == num_frames
         assert sinfo.bits_per_sample == bits_per_sample
         assert sinfo.encoding == get_encoding(ext, dtype)
+
+
+@skipIfNoSox
+class TestInfoNoSuchFile(PytorchTestCase):
+    def test_info_fail(self):
+        """
+        When attempted to get info on a non-existing file, error message must contain the file path.
+        """
+        path = "non_existing_audio.wav"
+        with self.assertRaisesRegex(RuntimeError, "^Error loading audio file: failed to open file {0}$".format(path)):
+            sox_io_backend.info(path)

test/torchaudio_unittest/backend/sox_io/load_test.py

@@ -522,3 +522,14 @@ class TestFileObjectHttp(HttpServerMixin, PytorchTestCase):
 
         assert sr == sample_rate
         self.assertEqual(expected, found)
+
+
+@skipIfNoSox
+class TestLoadNoSuchFile(PytorchTestCase):
+    def test_load_fail(self):
+        """
+        When attempted to load a non-existing file, error message must contain the file path.
+        """
+        path = "non_existing_audio.wav"
+        with self.assertRaisesRegex(RuntimeError, "^Error loading audio file: failed to open file {0}$".format(path)):
+            sox_io_backend.load(path)

test/torchaudio_unittest/backend/sox_io/save_test.py

 import io
+import os
 import unittest
 
+import torch
 from torchaudio.backend import sox_io_backend
 from parameterized import parameterized
 
@@ -387,3 +389,14 @@ class TestSaveParams(TempDirMixin, PytorchTestCase):
         sox_io_backend.save(path, data, 8000)
 
         self.assertEqual(data, expected)
+
+
+@skipIfNoSox
+class TestSaveNonExistingDirectory(PytorchTestCase):
+    def test_save_fail(self):
+        """
+        When attempted to save into a non-existing dir, error message must contain the file path.
+        """
+        path = os.path.join("non_existing_directory", "foo.wav")
+        with self.assertRaisesRegex(RuntimeError, "^Error saving audio file: failed to open file {0}$".format(path)):
+            sox_io_backend.save(path, torch.zeros(1, 1), 8000)

torchaudio/csrc/sox/effects.cpp

@@ -101,7 +101,7 @@ std::tuple<torch::Tensor, int64_t> apply_effects_file(
       /*encoding=*/nullptr,
       /*filetype=*/format.has_value() ? format.value().c_str() : nullptr));
 
-  validate_input_file(sf);
+  validate_input_file(sf, path);
 
   const auto dtype = get_dtype(sf->encoding.encoding, sf->signal.precision);
 
@@ -204,7 +204,7 @@ std::tuple<torch::Tensor, int64_t> apply_effects_fileobj(
       /*filetype=*/format.has_value() ? format.value().c_str() : nullptr));
 
   // In case of streamed data, length can be 0
-  validate_input_file(sf);
+  validate_input_memfile(sf);
 
   // Prepare output buffer
   std::vector<sox_sample_t> out_buffer;

torchaudio/csrc/sox/io.cpp

@@ -19,9 +19,7 @@ std::tuple<int64_t, int64_t, int64_t, int64_t, std::string> get_info_file(
       /*encoding=*/nullptr,
       /*filetype=*/format.has_value() ? format.value().c_str() : nullptr));
 
-  if (static_cast<sox_format_t*>(sf) == nullptr) {
-    throw std::runtime_error("Error opening audio file");
-  }
+  validate_input_file(sf, path);
 
   return std::make_tuple(
       static_cast<int64_t>(sf->signal.rate),
@@ -123,7 +121,8 @@ void save_audio_file(
       /*overwrite_permitted=*/nullptr));
 
   if (static_cast<sox_format_t*>(sf) == nullptr) {
-    throw std::runtime_error("Error saving audio file: failed to open file.");
+    throw std::runtime_error(
+        "Error saving audio file: failed to open file " + path);
   }
 
   torchaudio::sox_effects_chain::SoxEffectsChain chain(
@@ -177,7 +176,7 @@ std::tuple<int64_t, int64_t, int64_t, int64_t, std::string> get_info_fileobj(
       /*filetype=*/format.has_value() ? format.value().c_str() : nullptr));
 
   // In case of streamed data, length can be 0
-  validate_input_file(sf);
+  validate_input_memfile(sf);
 
   return std::make_tuple(
       static_cast<int64_t>(sf->signal.rate),

torchaudio/csrc/sox/utils.cpp

@@ -81,15 +81,20 @@ void SoxFormat::close() {
   }
 }
 
-void validate_input_file(const SoxFormat& sf) {
+void validate_input_file(const SoxFormat& sf, const std::string& path) {
   if (static_cast<sox_format_t*>(sf) == nullptr) {
-    throw std::runtime_error("Error loading audio file: failed to open file.");
+    throw std::runtime_error(
+        "Error loading audio file: failed to open file " + path);
   }
   if (sf->encoding.encoding == SOX_ENCODING_UNKNOWN) {
     throw std::runtime_error("Error loading audio file: unknown encoding.");
   }
 }
 
+void validate_input_memfile(const SoxFormat& sf) {
+  return validate_input_file(sf, "<in memory buffer>");
+}
+
 void validate_input_tensor(const torch::Tensor tensor) {
   if (!tensor.device().is_cpu()) {
     throw std::runtime_error("Input tensor has to be on CPU.");

torchaudio/csrc/sox/utils.h

@@ -56,7 +56,10 @@ struct SoxFormat {
 
 ///
 /// Verify that input file is found, has known encoding, and not empty
-void validate_input_file(const SoxFormat& sf);
+void validate_input_file(const SoxFormat& sf, const std::string& path);
+
+/// Verify that input memory buffer has known encoding, and not empty
+void validate_input_memfile(const SoxFormat& sf);
 
 ///
 /// Verify that input Tensor is 2D, CPU and either uin8, int16, int32 or float32