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अपनी प्राथमिकताओं के आधार पर, कॉन्टेंट को सेव करें और कैटगरी में बांटें.
टेंसरफ़्लो:: ऑप्स:: FakeQuantWithMinMaxVarsPerChannelGradient
#include <array_ops.h>
FakeQuantWithMinMaxVarsPerChannel ऑपरेशन के लिए ग्रेडिएंट की गणना करें।
सारांश
तर्क:
- स्कोप: एक स्कोप ऑब्जेक्ट
- ग्रेडिएंट्स: FakeQuantWithMinMaxVars ऑपरेशन के ऊपर बैकप्रॉपैगेटेड ग्रेडिएंट्स, इनमें से एक को आकार देते हैं:
[d]
, [b, d]
, [b, h, w, d]
। - इनपुट: FakeQuantWithMinMaxVars ऑपरेशन में इनपुट के रूप में पारित मान,
gradients
के समान आकार के होते हैं। न्यूनतम, अधिकतम: परिमाणीकरण अंतराल, आकार की फ़्लोट्स [d]
।
वैकल्पिक विशेषताएँ (देखें Attrs
):
- num_bits: परिमाणीकरण की बिटविड्थ; 2 और 16 के बीच, सम्मिलित।
- नैरो_रेंज: क्या मात्रा को 2^num_bits में विभाजित करना है - 1 अलग-अलग मान।
रिटर्न:
-
Output
बैकप्रॉप्स_wrt_input: बैकप्रॉपैगेटेड ग्रेडिएंट्स wrt इनपुट्स, आकार inputs
के समान: gradients * (inputs >= min && inputs <= max)
। -
Output
बैकप्रॉप_wrt_min: बैकप्रॉपैगेटेड ग्रेडिएंट्स wrt न्यूनतम पैरामीटर, आकार [d]
: sum_per_d(gradients * (inputs < min))
। -
Output
बैकप्रॉप_wrt_max: बैकप्रॉपैगेटेड ग्रेडिएंट्स wrt अधिकतम पैरामीटर, आकार [d]
: sum_per_d(gradients * (inputs > max))
।
सार्वजनिक गुण
सार्वजनिक समारोह
सार्वजनिक स्थैतिक कार्य
संकीर्ण रेंज
Attrs NarrowRange(
bool x
)
संख्या बिट्स
Attrs NumBits(
int64 x
)
जब तक कुछ अलग से न बताया जाए, तब तक इस पेज की सामग्री को Creative Commons Attribution 4.0 License के तहत और कोड के नमूनों को Apache 2.0 License के तहत लाइसेंस मिला है. ज़्यादा जानकारी के लिए, Google Developers साइट नीतियां देखें. Oracle और/या इससे जुड़ी हुई कंपनियों का, Java एक रजिस्टर किया हुआ ट्रेडमार्क है.
आखिरी बार 2025-07-26 (UTC) को अपडेट किया गया.
[null,null,["आखिरी बार 2025-07-26 (UTC) को अपडेट किया गया."],[],[],null,["# tensorflow::ops::FakeQuantWithMinMaxVarsPerChannelGradient Class Reference\n\ntensorflow::ops::FakeQuantWithMinMaxVarsPerChannelGradient\n==========================================================\n\n`#include \u003carray_ops.h\u003e`\n\nCompute gradients for a [FakeQuantWithMinMaxVarsPerChannel](/versions/r2.0/api_docs/cc/class/tensorflow/ops/fake-quant-with-min-max-vars-per-channel#classtensorflow_1_1ops_1_1_fake_quant_with_min_max_vars_per_channel) operation.\n\nSummary\n-------\n\nArguments:\n\n- scope: A [Scope](/versions/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope) object\n- gradients: Backpropagated gradients above the [FakeQuantWithMinMaxVars](/versions/r2.0/api_docs/cc/class/tensorflow/ops/fake-quant-with-min-max-vars#classtensorflow_1_1ops_1_1_fake_quant_with_min_max_vars) operation, shape one of: `[d]`, `[b, d]`, `[b, h, w, d]`.\n- inputs: Values passed as inputs to the [FakeQuantWithMinMaxVars](/versions/r2.0/api_docs/cc/class/tensorflow/ops/fake-quant-with-min-max-vars#classtensorflow_1_1ops_1_1_fake_quant_with_min_max_vars) operation, shape same as `gradients`. min, max: Quantization interval, floats of shape `[d]`.\n\n\u003cbr /\u003e\n\nOptional attributes (see [Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/fake-quant-with-min-max-vars-per-channel-gradient/attrs#structtensorflow_1_1ops_1_1_fake_quant_with_min_max_vars_per_channel_gradient_1_1_attrs)):\n\n- num_bits: The bitwidth of the quantization; between 2 and 16, inclusive.\n- narrow_range: Whether to quantize into 2\\^num_bits - 1 distinct values.\n\n\u003cbr /\u003e\n\nReturns:\n\n- [Output](/versions/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) backprops_wrt_input: Backpropagated gradients w.r.t. inputs, shape same as `inputs`: `gradients * (inputs \u003e= min && inputs \u003c= max)`.\n- [Output](/versions/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) backprop_wrt_min: Backpropagated gradients w.r.t. min parameter, shape `[d]`: `sum_per_d(gradients * (inputs \u003c min))`.\n- [Output](/versions/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) backprop_wrt_max: Backpropagated gradients w.r.t. max parameter, shape `[d]`: `sum_per_d(gradients * (inputs \u003e max))`.\n\n\u003cbr /\u003e\n\n| ### Constructors and Destructors ||\n|---|---|\n| [FakeQuantWithMinMaxVarsPerChannelGradient](#classtensorflow_1_1ops_1_1_fake_quant_with_min_max_vars_per_channel_gradient_1a7521d0f809a9a2bab753031ec59937a1)`(const ::`[tensorflow::Scope](/versions/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` gradients, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` inputs, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` min, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` max)` ||\n| [FakeQuantWithMinMaxVarsPerChannelGradient](#classtensorflow_1_1ops_1_1_fake_quant_with_min_max_vars_per_channel_gradient_1abf40f598a2e88d6f3a163fc6ac8c5a7d)`(const ::`[tensorflow::Scope](/versions/r2.0/api_docs/cc/class/tensorflow/scope#classtensorflow_1_1_scope)` & scope, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` gradients, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` inputs, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` min, ::`[tensorflow::Input](/versions/r2.0/api_docs/cc/class/tensorflow/input#classtensorflow_1_1_input)` max, const `[FakeQuantWithMinMaxVarsPerChannelGradient::Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/fake-quant-with-min-max-vars-per-channel-gradient/attrs#structtensorflow_1_1ops_1_1_fake_quant_with_min_max_vars_per_channel_gradient_1_1_attrs)` & attrs)` ||\n\n| ### Public attributes ||\n|-----------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------|\n| [backprop_wrt_max](#classtensorflow_1_1ops_1_1_fake_quant_with_min_max_vars_per_channel_gradient_1acc9bf06f7b09f2437e913f6f32f6dfe0) | `::`[tensorflow::Output](/versions/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n| [backprop_wrt_min](#classtensorflow_1_1ops_1_1_fake_quant_with_min_max_vars_per_channel_gradient_1ae7efb996b2e96e793a55decfaac3bfc4) | `::`[tensorflow::Output](/versions/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n| [backprops_wrt_input](#classtensorflow_1_1ops_1_1_fake_quant_with_min_max_vars_per_channel_gradient_1a99d7e4cadd3a7b374e246edb6cc207fe) | `::`[tensorflow::Output](/versions/r2.0/api_docs/cc/class/tensorflow/output#classtensorflow_1_1_output) |\n| [operation](#classtensorflow_1_1ops_1_1_fake_quant_with_min_max_vars_per_channel_gradient_1a2054be8cb0cdd3bc1c9721baa5cca289) | [Operation](/versions/r2.0/api_docs/cc/class/tensorflow/operation#classtensorflow_1_1_operation) |\n\n| ### Public static functions ||\n|-------------------------------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [NarrowRange](#classtensorflow_1_1ops_1_1_fake_quant_with_min_max_vars_per_channel_gradient_1a027f51a466b8dcf2dbff757b15dc7200)`(bool x)` | [Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/fake-quant-with-min-max-vars-per-channel-gradient/attrs#structtensorflow_1_1ops_1_1_fake_quant_with_min_max_vars_per_channel_gradient_1_1_attrs) |\n| [NumBits](#classtensorflow_1_1ops_1_1_fake_quant_with_min_max_vars_per_channel_gradient_1ad2357206b80cb845d85a727dcdd2d022)`(int64 x)` | [Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/fake-quant-with-min-max-vars-per-channel-gradient/attrs#structtensorflow_1_1ops_1_1_fake_quant_with_min_max_vars_per_channel_gradient_1_1_attrs) |\n\n| ### Structs ||\n|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| [tensorflow::ops::FakeQuantWithMinMaxVarsPerChannelGradient::Attrs](/versions/r2.0/api_docs/cc/struct/tensorflow/ops/fake-quant-with-min-max-vars-per-channel-gradient/attrs) | Optional attribute setters for [FakeQuantWithMinMaxVarsPerChannelGradient](/versions/r2.0/api_docs/cc/class/tensorflow/ops/fake-quant-with-min-max-vars-per-channel-gradient#classtensorflow_1_1ops_1_1_fake_quant_with_min_max_vars_per_channel_gradient). |\n\nPublic attributes\n-----------------\n\n### backprop_wrt_max\n\n```scdoc\n::tensorflow::Output backprop_wrt_max\n``` \n\n### backprop_wrt_min\n\n```scdoc\n::tensorflow::Output backprop_wrt_min\n``` \n\n### backprops_wrt_input\n\n```scdoc\n::tensorflow::Output backprops_wrt_input\n``` \n\n### operation\n\n```text\nOperation operation\n``` \n\nPublic functions\n----------------\n\n### FakeQuantWithMinMaxVarsPerChannelGradient\n\n```gdscript\n FakeQuantWithMinMaxVarsPerChannelGradient(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input gradients,\n ::tensorflow::Input inputs,\n ::tensorflow::Input min,\n ::tensorflow::Input max\n)\n``` \n\n### FakeQuantWithMinMaxVarsPerChannelGradient\n\n```gdscript\n FakeQuantWithMinMaxVarsPerChannelGradient(\n const ::tensorflow::Scope & scope,\n ::tensorflow::Input gradients,\n ::tensorflow::Input inputs,\n ::tensorflow::Input min,\n ::tensorflow::Input max,\n const FakeQuantWithMinMaxVarsPerChannelGradient::Attrs & attrs\n)\n``` \n\nPublic static functions\n-----------------------\n\n### NarrowRange\n\n```text\nAttrs NarrowRange(\n bool x\n)\n``` \n\n### NumBits\n\n```text\nAttrs NumBits(\n int64 x\n)\n```"]]