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Lazy tensor: automatically promote constants to inputs based on history #476
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66f7073
Automatically promote constants in lazy tensor trace.
bgogul ade0ed9
Do not promote equal constants.
bgogul 1cba36f
Add clearCache method and mark that cache is not thread safe.
bgogul 05971e3
Add test for constant promotion.
bgogul 8368e5d
Add test to check that we don't promote equal constants.
bgogul fd7a7de
Use TFE_Op("Equal") to compare tensors.
bgogul 4a56a97
Remove redundant test.
bgogul 3010625
autoConstPromotion -> constPromotion
bgogul 0249da8
Style fixes: common let, function arguments, etc.
bgogul 6455ac4
more fixes
bgogul db1ac09
Style fixes.
bgogul 7c3b9bd
Make Attribute and TFETensorHandle conform to Equatable.
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,158 @@ | ||
| // Copyright 2019 The TensorFlow Authors. All Rights Reserved. | ||
| // | ||
| // 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. | ||
| import CTensorFlow | ||
|
|
||
| extension TFETensorHandle: Equatable {} | ||
|
|
||
| public func ==(_ lhs: TFETensorHandle, _ rhs: TFETensorHandle) -> Bool { | ||
| return lhs._cTensorHandle == rhs._cTensorHandle | ||
| } | ||
|
|
||
| extension TFETensorHandle { | ||
| /// Returns true if the underlying tensors are equal. | ||
| func elementsEqual(_ other: TFETensorHandle) -> Bool { | ||
| let selfDtype = TFE_TensorHandleDataType(self._cTensorHandle) | ||
| let otherDtype = TFE_TensorHandleDataType(other._cTensorHandle) | ||
| precondition( | ||
| selfDtype == otherDtype && selfDtype != TF_VARIANT && selfDtype != TF_RESOURCE, | ||
| "Datatypes of tensor handles don't match.") | ||
| let op = TFE_Op("Equal", 1) | ||
| op.updateAttribute("T", TensorDataType(selfDtype)) | ||
| op.addInput(self) | ||
| op.addInput(other) | ||
| let result: Tensor<Bool> = op.execute(Int(1)) | ||
| return result.scalars.allSatisfy { $0 } | ||
| } | ||
| } | ||
|
|
||
| extension LazyTensorHandle { | ||
| func isEquivalent(to other: LazyTensorHandle) -> Bool { | ||
| switch (self.handle, other.handle) { | ||
| case let (.concrete(x, _), .concrete(y, _)): | ||
| return x == y | ||
| case let (.symbolic(x, xi, _), .symbolic(y, yi, _)): | ||
| return xi == yi && x.id == y.id | ||
| default: return false | ||
| } | ||
| } | ||
| } | ||
|
|
||
| extension LazyTensorOperation.Input { | ||
| /// Returns true if these inputs are equivalent when comparing lazy tensor traces. | ||
| func isEquivalent(to other: LazyTensorOperation.Input) -> Bool { | ||
| switch (self, other) { | ||
| case let (.single(l), .single(r)): | ||
| return l.isEquivalent(to: r) | ||
| case let (.list(l), .list(r)): | ||
| return l.elementsEqual(r, by: { $0.isEquivalent(to: $1) }) | ||
| default: | ||
| return false | ||
| } | ||
| } | ||
| } | ||
|
|
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| extension LazyTensorOperation { | ||
| /// Returns true if these operations are equivalent when comparing lazy tensor traces. | ||
| func isEquivalent(to other: LazyTensorOperation) -> Bool { | ||
| return self.name == other.name && | ||
| self.outputCount == other.outputCount && | ||
| self.deviceName == other.deviceName && | ||
| self.inputs.elementsEqual(other.inputs, by: { $0.isEquivalent(to: $1) }) && | ||
| self.attributes == other.attributes | ||
| } | ||
| } | ||
|
|
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| // TODO(TF-693): This is not thread safe! | ||
| struct LazyTensorTraceCache { | ||
| /// Cache from signature to traces that match signature. | ||
| static private var cache: [String: [LazyTensorTrace]] = [:] | ||
| static func clearCache() { cache.removeAll() } | ||
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| /// Returns a `MaterializationTraceInfo` with possibly some constants promoted to inputs. | ||
| static func traceWithPromotedConstants( | ||
| _ traceInfo: MaterializationTraceInfo | ||
| ) -> MaterializationTraceInfo { | ||
| let trace = traceInfo.trace | ||
| guard var traces = cache[trace.signature] else { | ||
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|
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| cache[trace.signature] = [trace] | ||
| return traceInfo | ||
| } | ||
| for cachedTrace in traces { | ||
| if let promotedTrace = traceInfo.withPromotedConstants(cachedTrace: cachedTrace) { | ||
| debugLog("Promoted: \(promotedTrace)\n") | ||
| return promotedTrace | ||
| } | ||
| } | ||
| // No match found; cache and return the input `traceInfo` itself. | ||
| traces.append(trace) | ||
| return traceInfo | ||
| } | ||
| } | ||
|
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||
| private extension MaterializationTraceInfo { | ||
| func withPromotedConstants(cachedTrace: LazyTensorTrace) -> MaterializationTraceInfo? { | ||
| let currentTrace = self.trace | ||
| if currentTrace.operations.count != cachedTrace.operations.count { return nil } | ||
| var promotableConstants: [(Int, TFETensorHandle)] = [] | ||
| for (i, current) in currentTrace.operations.enumerated() { | ||
| let cached = cachedTrace.operations[i] | ||
| if let (currentTensor, cachedTensor) = Self.promotableConstants(current, cached) { | ||
| if currentTensor.elementsEqual(cachedTensor) { continue } | ||
| promotableConstants.append((i, currentTensor)) | ||
| continue | ||
| } | ||
| // TODO: we might avoid running the following check based on results of promotableConstant | ||
| if current.isEquivalent(to: cached) { continue } | ||
| return nil | ||
| } | ||
|
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| let newConcreteInputs: [TFETensorHandle] = promotableConstants.map { return $0.1 } | ||
| let newOperations = currentTrace.operations | ||
| let newInputs = promotableConstants.map { | ||
| (promotableConstant: (Int, TFETensorHandle)) -> LazyTensorOperation in | ||
| let constantOp = newOperations[promotableConstant.0] | ||
| constantOp.name = "Placeholder" | ||
| constantOp.attributes.removeValue(forKey: "value") | ||
| return constantOp | ||
| } | ||
| let newTrace = LazyTensorTrace( | ||
| inputs: currentTrace.inputs + newInputs, | ||
| operations: newOperations, | ||
| outputs: currentTrace.outputs) | ||
| return MaterializationTraceInfo( | ||
| lazyOperations: self.lazyOperations, | ||
| trace: newTrace, | ||
| concreteInputs: self.concreteInputs + newConcreteInputs) | ||
| } | ||
|
|
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| /// If `current` and `cached` are compatible constants, returns the constant tensors. | ||
| static private func promotableConstants( | ||
| _ current: LazyTensorOperation, | ||
| _ cached: LazyTensorOperation | ||
| ) -> (TFETensorHandle, TFETensorHandle)? { | ||
| if current.name != "Const" || cached.name != "Const" { return nil } | ||
| let currentValue = current.attributes["value"]! | ||
| let cachedValue = cached.attributes["value"]! | ||
| guard case let .constTensor(currentTensor) = currentValue, | ||
| case let .constTensor(cachedTensor) = cachedValue | ||
| else { return nil } | ||
| let currentDtype = TFE_TensorHandleDataType(currentTensor._cTensorHandle) | ||
| let cachedDtype = TFE_TensorHandleDataType(cachedTensor._cTensorHandle) | ||
| if currentDtype == TF_VARIANT || currentDtype == TF_RESOURCE { return nil } | ||
| if cachedDtype == TF_VARIANT || cachedDtype == TF_RESOURCE { return nil } | ||
| return currentTensor.shape == cachedTensor.shape && currentDtype == cachedDtype | ||
| ? (currentTensor, cachedTensor) | ||
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|
||
| : nil | ||
| } | ||
| } | ||
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,131 @@ | ||
| // Copyright 2019 The TensorFlow Authors. All Rights Reserved. | ||
| // | ||
| // 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. | ||
|
|
||
| import XCTest | ||
|
|
||
| @testable import TensorFlow | ||
| import CTensorFlow | ||
|
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| final class LazyTensorTraceCacheTests: LazyTensorTestCase { | ||
| override class func setUp() { | ||
| super.setUp() | ||
| LazyTensorContext.local.shouldPromoteConstants = true | ||
| } | ||
|
|
||
| override class func tearDown() { | ||
| super.tearDown() | ||
| LazyTensorTraceCache.clearCache() | ||
| } | ||
|
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| func testConstPromotion() { | ||
| LazyTensorTraceCache.clearCache() | ||
| let a = Tensor<Float>(1.0) | ||
| let b = Tensor<Float>(2.0) | ||
| let c = Tensor<Float>(3.0) | ||
| let d = Tensor<Float>(4.0) | ||
| let w = a * b | ||
| let x = c * d | ||
| // Trigger materialization for `w` so that a trace with constants and mul is added to cache. | ||
| XCTAssertEqual( | ||
| lazyTrace(w).description, | ||
| """ | ||
| lazyTrace_3() -> (%2) { | ||
| %0 = Const[dtype: float, value: 1.0]() | ||
| %1 = Const[dtype: float, value: 2.0]() | ||
| %2 = Mul[T: float](%0, %1) | ||
| } | ||
| """) | ||
| XCTAssertEqual(w.scalars, [2.0]) | ||
|
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| // The trace for `x` should have the inputs to Mul as arguments instead of constants. | ||
| XCTAssertEqual( | ||
| lazyTrace(x).description, | ||
| """ | ||
| lazyTrace_3(%0: float, %1: float) -> (%2) { | ||
| %2 = Mul[T: float](%0, %1) | ||
| } | ||
| """) | ||
| XCTAssertEqual(x.scalarized(), 12.0) | ||
|
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||
| let e = Tensor<Float>(shape: [1,3], scalars: [1, 2, 3]) | ||
| let f = Tensor<Float>(5.0) | ||
| let y = e * f | ||
| // We won't promote constants in 'y' as shape of constants is different. | ||
| XCTAssertEqual( | ||
| lazyTrace(y).description, | ||
| """ | ||
| lazyTrace_3() -> (%2) { | ||
| %0 = Const[dtype: float, value: [[1.0, 2.0, 3.0]]]() | ||
| %1 = Const[dtype: float, value: 5.0]() | ||
| %2 = Mul[T: float](%0, %1) | ||
| } | ||
| """) | ||
| XCTAssertEqual(y.scalars, [5.0, 10.0, 15.0]) | ||
| } | ||
|
|
||
| func testDoNotPromoteEqualConstants() { | ||
| LazyTensorTraceCache.clearCache() | ||
| let a = Tensor<Float>(1.0) | ||
| let b = Tensor<Float>(2.0) | ||
| let c = Tensor<Float>(3.0) | ||
| let w = a * b | ||
| let x = a * c | ||
| XCTAssertEqual( | ||
| lazyTrace(w).description, | ||
| """ | ||
| lazyTrace_3() -> (%2) { | ||
| %0 = Const[dtype: float, value: 1.0]() | ||
| %1 = Const[dtype: float, value: 2.0]() | ||
| %2 = Mul[T: float](%0, %1) | ||
| } | ||
| """) | ||
| XCTAssertEqual(w.scalars, [2.0]) | ||
| // Const 1.0 is not promoted. | ||
| XCTAssertEqual( | ||
| lazyTrace(x).description, | ||
| """ | ||
| lazyTrace_3(%1: float) -> (%2) { | ||
| %0 = Const[dtype: float, value: 1.0]() | ||
| %2 = Mul[T: float](%0, %1) | ||
| } | ||
| """) | ||
| } | ||
|
|
||
| private func lazyTensorOperation<T: TensorFlowScalar>( | ||
| _ input: Tensor<T> | ||
| ) -> LazyTensorOperation? { | ||
| let tensor = input.handle.handle | ||
| guard let lazyTensor = tensor as? LazyTensorHandle else { | ||
| XCTFail("Trying to get lazy trace for a non-lazy tensor.") | ||
| return nil | ||
| } | ||
| guard case let .symbolic(lazyOp, _, _) = lazyTensor.handle else { | ||
| XCTFail("Cannot get lazy trace for a concrete tensor.") | ||
| return nil | ||
| } | ||
| return lazyOp | ||
| } | ||
|
|
||
| private func lazyTrace<T: TensorFlowScalar>( | ||
| _ input: Tensor<T> | ||
| ) -> LazyTensorTrace { | ||
| let lazyOperation = lazyTensorOperation(input)! | ||
| return LazyTensorTraceBuilder.materializationTraceInfo(lazyOperation).trace | ||
| } | ||
|
|
||
| static var allTests = [ | ||
| ("testConstPromotion", testConstPromotion), | ||
| ("testDoNotPromoteEqualConstants", testDoNotPromoteEqualConstants) | ||
| ] | ||
| } |
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