Refactors onnx import adding better support for image functions #9466
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| Original file line number | Diff line number | Diff line change |
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@@ -241,7 +241,7 @@ fun SDImage() = Namespace("Image"){ | |
| Arg(BOOL, "preserveAspectRatio") { description = "Whether to preserve the aspect ratio." + | ||
| " If this is set, then images will be resized to a size that fits in size while preserving the aspect ratio" + | ||
| " of the original image. Scales up the image if size is bigger than the current size of the image. Defaults to False."; defaultValue=false; } | ||
| Arg(BOOL, "antialias") { description = "Whether to use an anti-aliasing filter when downsampling an image"; defaultValue=false; } | ||
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| Arg(ENUM, "ImageResizeMethod") { possibleValues = listOf( "ResizeBilinear", "ResizeBicubic", "ResizeNearest", "ResizeGaussian", | ||
| "ResizeLanczos5", "ResizeMitchelcubic", "ResizeArea"); description = "ResizeBilinear: Bilinear interpolation. If 'antialias' is true, becomes a hat/tent filter function with radius 1 when downsampling.\n" + | ||
| "ResizeLanczos5: Lanczos kernel with radius 5. Very-high-quality filter but may have stronger ringing.\n" + | ||
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@@ -259,4 +259,36 @@ fun SDImage() = Namespace("Image"){ | |
| """.trimIndent() | ||
| } | ||
| } | ||
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| Op("resizeBiLinear") { | ||
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There was a problem hiding this comment. @treo new op for bi linear image resize. |
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| javaPackage = "org.nd4j.linalg.api.ops.impl.image" | ||
| javaOpClass = "ResizeBilinear" | ||
| Input(NUMERIC,"input") { description = "4D image"} | ||
| Arg(INT ,"height") { description = "target height for resizing to "} | ||
| Arg(INT ,"width") { description = "target width for resizing to"} | ||
| Arg(BOOL ,"alignCorners") { description = "whether to align corners during resizing. Images are aligned to preserve corners."} | ||
| Arg(BOOL,"halfPixelCenters") { description = "When resizing, assumes pixels are centered at 0.5."} | ||
| Output(NUMERIC, "output"){ description = "Output image" } | ||
| Doc(Language.ANY, DocScope.ALL){ | ||
| """ | ||
| Resize images to size using the specified method. | ||
| """.trimIndent() | ||
| } | ||
| } | ||
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| Op("resizeBiCubic") { | ||
| javaPackage = "org.nd4j.linalg.api.ops.impl.image" | ||
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There was a problem hiding this comment. @treo same for bicubic |
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| javaOpClass = "ResizeBicubic" | ||
| Input(NUMERIC,"input") { description = "4D image"} | ||
| Input(INT ,"size") { description = "the target size to resize to "} | ||
| Arg(BOOL ,"alignCorners") { description = "whether to align corners during resizing. Images are aligned to preserve corners."} | ||
| Arg(BOOL,"alignPixelCenters") { description = "When resizing, assumes pixels are centered at 0.5."} | ||
| Output(NUMERIC, "output"){ description = "Output image" } | ||
| Doc(Language.ANY, DocScope.ALL){ | ||
| """ | ||
| Resize images to size using the specified method. | ||
| """.trimIndent() | ||
| } | ||
| } | ||
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| } | ||
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@@ -24,6 +24,7 @@ | |
| package org.nd4j.codegen.ops | ||
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| import org.nd4j.codegen.api.AtLeast | ||
| import org.nd4j.codegen.api.DataType | ||
| import org.nd4j.codegen.api.Language | ||
| import org.nd4j.codegen.api.doc.DocScope | ||
| import org.nd4j.codegen.dsl.* | ||
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@@ -480,6 +481,38 @@ fun SDBaseOps() = Namespace("BaseOps"){ | |
| } | ||
| } | ||
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| Op("sparseToDense") { | ||
| javaPackage = "org.nd4j.linalg.api.ops.compat" | ||
| javaOpClass = "CompatSparseToDense" | ||
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There was a problem hiding this comment. @treo sparse to dense is also a new op. Used in model import and works fine, just never fully mapped or exposed. |
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| Input(NUMERIC, "indices") { description = "The indices of the sparse matrix" } | ||
| Input(NUMERIC, "shape") { description = "The output shape" } | ||
| Input(NUMERIC, "values") { description = "The values for the array" } | ||
| Output(NUMERIC, "output"){ description = "Populated dense INDArray with given values and indices" } | ||
| Doc(Language.ANY, DocScope.ALL){ | ||
| """ | ||
| Create a dense matrix equivalent of a sparse matrix based on the given input. | ||
| """.trimIndent() | ||
| } | ||
| } | ||
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| Op("sparseToDense") { | ||
| javaPackage = "org.nd4j.linalg.api.ops.compat" | ||
| javaOpClass = "CompatSparseToDense" | ||
| Input(NUMERIC, "indices") { description = "The indices of the sparse matrix" } | ||
| Input(NUMERIC, "shape") { description = "The output shape" } | ||
| Input(NUMERIC, "values") { description = "The values for the array" } | ||
| Input(NUMERIC,"defaultValue") { description = "Default value" } | ||
| Output(NUMERIC, "output"){ description = "Populated dense INDArray with given values and indices" } | ||
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| Doc(Language.ANY, DocScope.ALL){ | ||
| """ | ||
| Create a dense matrix equivalent of a sparse matrix based on the given input. | ||
| """.trimIndent() | ||
| } | ||
| } | ||
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| Op("lt") { | ||
| javaPackage = "org.nd4j.linalg.api.ops.impl.scalar.comparison" | ||
| javaOpClass = "ScalarLessThan" | ||
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@@ -588,6 +621,63 @@ fun SDBaseOps() = Namespace("BaseOps"){ | |
| useMixin(keepDimsDoc) | ||
| } | ||
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| Op("whereNumpy") { | ||
| javaPackage = "org.nd4j.linalg.api.ops.impl.controlflow" | ||
| javaOpClass = "WhereNumpy" | ||
| Input(NUMERIC, "x") { description = "The first array" } | ||
|
There was a problem hiding this comment. @treo we've always had 2 where implementations: I'm exposing both here and letting user pick. |
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| Input(NUMERIC, "y") { description = "The second array" } | ||
| Input(NUMERIC, "condition") { description = "Condition array determining which elements at which indices should be picked from. If true, picks from x, other wise y" } | ||
| Output(NUMERIC, "output"){ description = "Number of elements that the condition is satisfied for" } | ||
| Doc(Language.ANY, DocScope.ALL){ | ||
| """ | ||
| As implemented in numpy, Return elements chosen from x or y depending on condition. | ||
| """.trimIndent() | ||
| } | ||
| useMixin(keepDimsDoc) | ||
| } | ||
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| Op("where") { | ||
| javaPackage = "org.nd4j.linalg.api.ops.impl.controlflow" | ||
| javaOpClass = "Where" | ||
| Input(NUMERIC, "x") { description = "The first array" } | ||
| Input(NUMERIC, "y") { description = "The second array" } | ||
| Input(BOOL, "condition") { description = "Condition array determining which elements at which indices should be picked from. If true, picks from x, other wise y" } | ||
| Output(NUMERIC, "output"){ description = "Number of elements that the condition is satisfied for" } | ||
| Doc(Language.ANY, DocScope.ALL){ | ||
| """ | ||
| Similar to numpy where, takes elements from x or y depending on whether the condition at a given element is true or false | ||
| """.trimIndent() | ||
| } | ||
| useMixin(keepDimsDoc) | ||
| } | ||
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| Op("where") { | ||
| javaPackage = "org.nd4j.linalg.api.ops.impl.controlflow" | ||
| javaOpClass = "Where" | ||
| Input(NUMERIC, "x") { description = "The first array" } | ||
| Input(BOOL, "condition") { description = "Condition array determining which elements at which indices should be picked from. If true, picks from x, other wise y" } | ||
| Output(NUMERIC, "output"){ description = "Number of elements that the condition is satisfied for" } | ||
| Doc(Language.ANY, DocScope.ALL){ | ||
| """ | ||
| Similar to numpy where, takes elements from x or y depending on whether the condition at a given element is true or false | ||
| """.trimIndent() | ||
| } | ||
| useMixin(keepDimsDoc) | ||
| } | ||
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| Op("where") { | ||
| javaPackage = "org.nd4j.linalg.api.ops.impl.controlflow" | ||
| javaOpClass = "Where" | ||
| Input(BOOL, "condition") { description = "Condition array determining which elements at which indices should be picked from. If true, picks from x, other wise y" } | ||
| Output(NUMERIC, "output"){ description = "Number of elements that the condition is satisfied for" } | ||
| Doc(Language.ANY, DocScope.ALL){ | ||
| """ | ||
| Returns elements that are true from the given condition array | ||
| """.trimIndent() | ||
| } | ||
| useMixin(keepDimsDoc) | ||
| } | ||
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| Op("max") { | ||
| javaPackage = "org.nd4j.linalg.api.ops.impl.reduce.same" | ||
| legacy = true | ||
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@@ -819,6 +909,25 @@ fun SDBaseOps() = Namespace("BaseOps"){ | |
| } | ||
| } | ||
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| Op("create") { | ||
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There was a problem hiding this comment. @treo this is the only op we have for anything like "ones" or "zeros" |
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| javaPackage = "org.nd4j.linalg.api.ops.impl.shape" | ||
| javaOpClass = "Create" | ||
| Input(NUMERIC, "shape") { description = "Input INDArray " } | ||
| Arg(DATA_TYPE,"dataType") {description = "Data type of array"} | ||
| //note when generating strings you need to add quotes as well or it's generated incorrectly | ||
| Arg(STRING,"order") {description = "Order of array "; defaultValue="\"c\""} | ||
| Arg(BOOL,"initialize") {description = "Whether to initialize the array or not "; defaultValue=false} | ||
| Output(NUMERIC, "output"){ description = "A new INDArray with the same (dynamic) shape as the input" } | ||
| Doc(Language.ANY, DocScope.ALL){ | ||
| """ | ||
| Return a newly created variable, with the specified shape and data type. | ||
| """.trimIndent() | ||
| } | ||
| } | ||
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| Op("onesLike") { | ||
| javaPackage = "org.nd4j.linalg.api.ops.impl.shape" | ||
| Input(NUMERIC, "input") { description = "Input INDArray " } | ||
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@@ -1388,7 +1497,7 @@ fun SDBaseOps() = Namespace("BaseOps"){ | |
| Output(NUMERIC, "output"){ description = "reduced array of rank (input rank - num dimensions)" } | ||
| Doc(Language.ANY, DocScope.ALL){ | ||
| """ | ||
| Standard deviation array reduction operation, optionally along specified dimensions | ||
| """.trimIndent() | ||
| } | ||
| useMixin(keepDimsDoc) | ||
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@@ -1420,6 +1529,36 @@ fun SDBaseOps() = Namespace("BaseOps"){ | |
| } | ||
| } | ||
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| Op("stridedSlice") { | ||
| javaPackage = "org.nd4j.linalg.api.ops.impl.shape" | ||
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There was a problem hiding this comment. @treo new op: just exposing what's already there. A minor pain was the default values for the masks but I got that worked out. |
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| Input(NUMERIC, "in") { description = "Variable to get subset of" } | ||
| Input(NUMERIC, "begin") { description = "The beginning indices for the slice" } | ||
| Input(NUMERIC, "end") { description = "The ending indicesof the slice" } | ||
| Input(NUMERIC, "strides") { description = "The strides for each dimension" } | ||
| Arg(INT, "beginMask") { description = "Bit mask: If the ith bit is set to 1, then the value in the begin long[] is ignored, and a value of 0 is used instead for the beginning index for that dimension"; defaultValue=0 } | ||
| Arg(INT, "endMask") { description = "Bit mask: If the ith bit is set to 1, then the value in the end long[] is ignored, and a value of size(i)-1 is used instead for the end index for that dimension"; defaultValue=0 } | ||
| Arg(INT, "ellipsisMask") { description = "Bit mask: only one non-zero value is allowed here. If a non-zero value is set, then other dimensions are inserted as required at the specified position"; defaultValue=0 } | ||
| Arg(INT, "newAxisMask") { description = "Bit mask: if the ith bit is set to 1, then the begin/end/stride values are ignored, and a size 1 dimension is inserted at this point"; defaultValue=0 } | ||
| Arg(INT, "shrinkAxisMask") { description = "Bit mask: if the ith bit is set to 1, then the begin/end/stride values are ignored, and a size 1 dimension is removed at this point. Note that begin/end/stride values must result in a size 1 output for these dimensions"; defaultValue=0 } | ||
| Output(NUMERIC, "output"){ description = "A subset of the input array" } | ||
| Doc(Language.ANY, DocScope.ALL){ | ||
| """ | ||
| Get a subset of the specified input, by specifying the first element, last element, and the strides. | ||
| For example, if input is: | ||
| [a, b, c] | ||
| [d, e, f] | ||
| [g, h, i] | ||
| then stridedSlice(input, begin=[0,1], end=[2,2], strides=[2,1], all masks = 0) will return: | ||
| [b, c] | ||
| [h, i] | ||
| """.trimIndent() | ||
| } | ||
| } | ||
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| Op("sum") { | ||
| javaPackage = "org.nd4j.linalg.api.ops.impl.reduce.same" | ||
| legacy = true | ||
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@@ -1446,7 +1585,7 @@ fun SDBaseOps() = Namespace("BaseOps"){ | |
| Doc(Language.ANY, DocScope.ALL){ | ||
| """ | ||
| Switch operation | ||
| Predicate - if false, values are output to left (first) branch/output; if true, to right (second) branch/output | ||
| """.trimIndent() | ||
| } | ||
| } | ||
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@@ -1605,6 +1744,9 @@ fun SDBaseOps() = Namespace("BaseOps"){ | |
| useMixin(keepDimsDoc) | ||
| } | ||
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| Op("zerosLike") { | ||
| javaPackage = "org.nd4j.linalg.api.ops.impl.shape" | ||
| Input(NUMERIC, "input") { description = "Input " } | ||
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| Original file line number | Diff line number | Diff line change |
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@@ -2593,6 +2593,9 @@ public SDVariable one(String name, int... shape) { | |
| return one(name, Nd4j.defaultFloatingPointType(), shape); | ||
| } | ||
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| /** | ||
| * See {@link #one(String, DataType, long...)}. | ||
| * Creates a constant - i.e., CONSTANT type SDVariable. | ||
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@@ -2987,9 +2990,6 @@ public SDVariable var(INDArray arr) { | |
| public SDVariable var(String name, @NonNull INDArray arr) { | ||
| if (variables.containsKey(name) && variables.get(name).getVariable().getArr() != null) | ||
| throw new IllegalArgumentException("Another variable with the name " + name + " already exists."); | ||
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There was a problem hiding this comment. @treo this was removed because it disallowed booleans among other things for variable creation. There was a problem hiding this comment. In what context do non-fp variables make even sense? There was a problem hiding this comment. In my import use case, booleans and strings. There was a problem hiding this comment. eg: We've been supporting strings and booleans for a while and can run string manipulation among other ops that are not numeric. Var shouldn't always have to be just trainable parameters it could be ETL. |
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| Preconditions.checkArgument(!arr.isEmpty(), "Empty arrays cannot be used when creating variables. Array shape: %ndShape", arr); | ||
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| if (name == null || name.length() < 1) | ||
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@treo codegen copyright update