Java Code Examples for org.nd4j.linalg.factory.Nd4j#readBinary()
The following examples show how to use
org.nd4j.linalg.factory.Nd4j#readBinary() .
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Example 1
Source File: ArraySavingListener.java From deeplearning4j with Apache License 2.0 | 4 votes |
public static void compare(File dir1, File dir2, double eps) throws Exception { File[] files1 = dir1.listFiles(); File[] files2 = dir2.listFiles(); Preconditions.checkNotNull(files1, "No files in directory 1: %s", dir1); Preconditions.checkNotNull(files2, "No files in directory 2: %s", dir2); Preconditions.checkState(files1.length == files2.length, "Different number of files: %s vs %s", files1.length, files2.length); Map<String,File> m1 = toMap(files1); Map<String,File> m2 = toMap(files2); for(File f : files1){ String name = f.getName(); String varName = name.substring(name.indexOf('_') + 1, name.length()-4); //Strip "x_" and ".bin" File f2 = m2.get(varName); INDArray arr1 = Nd4j.readBinary(f); INDArray arr2 = Nd4j.readBinary(f2); //TODO String arrays won't work here! boolean eq = arr1.equalsWithEps(arr2, eps); if(eq){ System.out.println("Equals: " + varName.replaceAll("__", "/")); } else { if(arr1.dataType() == DataType.BOOL){ INDArray xor = Nd4j.exec(new Xor(arr1, arr2)); int count = xor.castTo(DataType.INT).sumNumber().intValue(); System.out.println("FAILS: " + varName.replaceAll("__", "/") + " - boolean, # differences = " + count); System.out.println("\t" + f.getAbsolutePath()); System.out.println("\t" + f2.getAbsolutePath()); xor.close(); } else { INDArray sub = arr1.sub(arr2); INDArray diff = Nd4j.math.abs(sub); double maxDiff = diff.maxNumber().doubleValue(); System.out.println("FAILS: " + varName.replaceAll("__", "/") + " - max difference = " + maxDiff); System.out.println("\t" + f.getAbsolutePath()); System.out.println("\t" + f2.getAbsolutePath()); sub.close(); diff.close(); } } arr1.close(); arr2.close(); } }
Example 2
Source File: Nd4jValidator.java From deeplearning4j with Apache License 2.0 | 4 votes |
/** * Validate whether the file represents a valid INDArray (of one of the allowed/specified data types) saved previously * with {@link Nd4j#saveBinary(INDArray, File)} to be read with {@link Nd4j#readBinary(File)} * * @param f File that should represent an INDArray saved with Nd4j.saveBinary * @param allowableDataTypes May be null. If non-null, the file must represent one of the specified data types * @return Result of validation */ public static ValidationResult validateINDArrayFile(@NonNull File f, DataType... allowableDataTypes) { ValidationResult vr = Nd4jCommonValidator.isValidFile(f, "INDArray File", false); if (vr != null && !vr.isValid()) { vr.setFormatClass(INDArray.class); return vr; } //TODO let's do this without reading the whole thing into memory - check header + length... try (INDArray arr = Nd4j.readBinary(f)) { //Using the fact that INDArray.close() exists -> deallocate memory as soon as reading is done if (allowableDataTypes != null) { ArrayUtils.contains(allowableDataTypes, arr.dataType()); } } catch (IOException e) { return ValidationResult.builder() .valid(false) .formatType("INDArray File") .formatClass(INDArray.class) .path(Nd4jCommonValidator.getPath(f)) .issues(Collections.singletonList("Unable to read file (IOException)")) .exception(e) .build(); } catch (Throwable t) { if (t instanceof OutOfMemoryError || t.getMessage().toLowerCase().contains("failed to allocate")) { //This is a memory exception during reading... result is indeterminant (might be valid, might not be, can't tell here) return ValidationResult.builder() .valid(true) .formatType("INDArray File") .formatClass(INDArray.class) .path(Nd4jCommonValidator.getPath(f)) .build(); } return ValidationResult.builder() .valid(false) .formatType("INDArray File") .formatClass(INDArray.class) .path(Nd4jCommonValidator.getPath(f)) .issues(Collections.singletonList("File may be corrupt or is not a binary INDArray file")) .exception(t) .build(); } return ValidationResult.builder() .valid(true) .formatType("INDArray File") .formatClass(INDArray.class) .path(Nd4jCommonValidator.getPath(f)) .build(); }
Example 3
Source File: DistributionStats.java From nd4j with Apache License 2.0 | 2 votes |
/** * Load distribution statistics from the file system * * @param meanFile file containing the means * @param stdFile file containing the standard deviations */ public static DistributionStats load(@NonNull File meanFile, @NonNull File stdFile) throws IOException { return new DistributionStats(Nd4j.readBinary(meanFile), Nd4j.readBinary(stdFile)); }
Example 4
Source File: StandardScaler.java From nd4j with Apache License 2.0 | 2 votes |
/** * Load the given mean and std * @param mean the mean file * @param std the std file * @throws IOException */ public void load(File mean, File std) throws IOException { this.mean = Nd4j.readBinary(mean); this.std = Nd4j.readBinary(std); }
Example 5
Source File: DistributionStats.java From deeplearning4j with Apache License 2.0 | 2 votes |
/** * Load distribution statistics from the file system * * @param meanFile file containing the means * @param stdFile file containing the standard deviations */ public static DistributionStats load(@NonNull File meanFile, @NonNull File stdFile) throws IOException { return new DistributionStats(Nd4j.readBinary(meanFile), Nd4j.readBinary(stdFile)); }
Example 6
Source File: StandardScaler.java From deeplearning4j with Apache License 2.0 | 2 votes |
/** * Load the given mean and std * @param mean the mean file * @param std the std file * @throws IOException */ public void load(File mean, File std) throws IOException { this.mean = Nd4j.readBinary(mean); this.std = Nd4j.readBinary(std); }